Unnamed: 0.1 int64 0 41k | Unnamed: 0 int64 0 41k | author stringlengths 9 1.39k | id stringlengths 11 18 | summary stringlengths 25 3.66k | title stringlengths 4 258 | year int64 1.99k 2.02k | arxiv_url stringlengths 32 39 | info stringlengths 523 3.18k | embeddings stringlengths 16.9k 17.1k |
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40,300 | 40,300 | ['Gabriele Costante', 'Thomas A. Ciarfuglia', 'Filippo Biondi'] | 1803.05387v1 | Synthetic aperture radar (SAR) interferometry (InSAR) is performed using
repeat-pass geometry. InSAR technique is used to estimate the topographic
reconstruction of the earth surface. The main problem of the range-Doppler
focusing technique is the nature of the two-dimensional SAR result, affected by
the layover indete... | Towards Monocular Digital Elevation Model (DEM) Estimation by
Convolutional Neural Networks - Application on Synthetic Aperture Radar
Images | 2,018 | http://arxiv.org/pdf/1803.05387v1 | Title Towards Monocular Digital Elevation Model DEM Estimation Convolutional Neural Networks Application Synthetic Aperture Radar Images Summary Synthetic aperture radar SAR interferometry InSAR performed using repeatpass geometry InSAR technique used estimate topographic reconstruction earth surface main problem range... | [-0.0032457823399454355, 0.045907266438007355, 0.012687092646956444, 0.020821239799261093, -0.023348921909928322, -0.00867654848843813, 0.03996486961841583, -0.08528749644756317, 0.011712058447301388, 0.02291690744459629, 0.033053476363420486, 0.0002629818918649107, 0.03761046752333641, 0.03424076363444328, 0.037653740... |
40,301 | 40,301 | ['Abhijit Suprem', 'Polo Chau'] | 1803.05401v1 | Traditional image recognition involves identifying the key object in a
portrait-type image with a single object focus (ILSVRC, AlexNet, and VGG). More
recent approaches consider dense image recognition - segmenting an image with
appropriate bounding boxes and performing image recognition within these
bounding boxes (Se... | Approximate Query Matching for Image Retrieval | 2,018 | http://arxiv.org/pdf/1803.05401v1 | Title Approximate Query Matching Image Retrieval Summary Traditional image recognition involves identifying key object portraittype image single object focus ILSVRC AlexNet VGG recent approach consider dense image recognition segmenting image appropriate bounding box performing image recognition within bounding box Sem... | [0.045133523643016815, 0.058224644511938095, 0.016127409413456917, 0.03644252568483353, -0.04928778111934662, 0.01658487692475319, -0.022802522405982018, 0.07201157510280609, 0.012096905149519444, -0.031942691653966904, -0.007247895002365112, -0.022945387288928032, -0.01523282378911972, 0.07961238920688629, -0.00302958... |
40,302 | 40,302 | ['Zihao Liu', 'Qi Liu', 'Tao Liu', 'Yanzhi Wang', 'Wujie Wen'] | 1803.05787v1 | Deep Neural Networks (DNNs) have achieved remarkable performance in a myriad
of realistic applications. However, recent studies show that well-trained DNNs
can be easily misled by adversarial examples (AE) -- the maliciously crafted
inputs by introducing small and imperceptible input perturbations. Existing
mitigation ... | Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial
Examples | 2,018 | http://arxiv.org/pdf/1803.05787v1 | Title Feature Distillation DNNOriented JPEG Compression Adversarial Examples Summary Deep Neural Networks DNNs achieved remarkable performance myriad realistic application However recent study show welltrained DNNs easily misled adversarial example AE maliciously crafted input introducing small imperceptible input pert... | [-0.002842595102265477, 0.060864925384521484, -0.023745276033878326, 0.03625476732850075, -0.027896687388420105, -0.019662396982312202, 0.03063654527068138, 0.018236763775348663, -0.0490865483880043, -0.0003243805840611458, 0.00566418282687664, 0.043020449578762054, 0.012709062546491623, 0.06239322945475578, 0.00588309... |
40,303 | 40,303 | ['Andrawes Al Bahou', 'Geethan Karunaratne', 'Renzo Andri', 'Lukas Cavigelli', 'Luca Benini'] | 1803.05849v1 | Deploying state-of-the-art CNNs requires power-hungry processors and off-chip
memory. This precludes the implementation of CNNs in low-power embedded
systems. Recent research shows CNNs sustain extreme quantization, binarizing
their weights and intermediate feature maps, thereby saving 8-32\x memory and
collapsing ener... | XNORBIN: A 95 TOp/s/W Hardware Accelerator for Binary Convolutional
Neural Networks | 2,018 | http://arxiv.org/pdf/1803.05849v1 | Title XNORBIN 95 TOpsW Hardware Accelerator Binary Convolutional Neural Networks Summary Deploying stateoftheart CNNs requires powerhungry processor offchip memory precludes implementation CNNs lowpower embedded system Recent research show CNNs sustain extreme quantization binarizing weight intermediate feature map the... | [0.009350192733108997, -0.0035872256848961115, 0.0019587052520364523, 0.06710189580917358, -0.03965176269412041, -0.03472931683063507, 0.03256578370928764, -0.00030934831011109054, -0.05219540745019913, 0.016051048412919044, -0.007374897599220276, 0.03339496627449989, 0.004483254626393318, 0.0766819417476654, 0.0284997... |
40,304 | 40,304 | ['E. Jared Shamwell', 'Sarah Leung', 'William D. Nothwang'] | 1803.05850v1 | We present an unsupervised deep neural network approach to the fusion of
RGB-D imagery with inertial measurements for absolute trajectory estimation.
Our network, dubbed the Visual-Inertial-Odometry Learner (VIOLearner), learns
to perform visual-inertial odometry (VIO) without inertial measurement unit
(IMU) intrinsic ... | Vision-Aided Absolute Trajectory Estimation Using an Unsupervised Deep
Network with Online Error Correction | 2,018 | http://arxiv.org/pdf/1803.05850v1 | Title VisionAided Absolute Trajectory Estimation Using Unsupervised Deep Network Online Error Correction Summary present unsupervised deep neural network approach fusion RGBD imagery inertial measurement absolute trajectory estimation network dubbed VisualInertialOdometry Learner VIOLearner learns perform visualinertia... | [-0.023233842104673386, 0.052924491465091705, 0.024819402024149895, 0.07442616671323776, 0.035137027502059937, 0.01685929112136364, -0.05811760574579239, -0.03170913830399513, -0.041455019265413284, 0.01593574695289135, 0.015351415611803532, 0.05195055529475212, 0.040568895637989044, 0.021266382187604904, 0.01075003482... |
40,305 | 40,305 | ['Aarti Jajoo', 'Matthew Nicol', 'Jaime Gateno', 'Ken-Chung Chen', 'Zhen Tang', 'Tasadduk Chowdhury', 'Jainfu Li', 'Steve Goufang Shen', 'James J. Xia'] | 1803.05853v1 | It is difficult to estimate the midsagittal plane of human subjects with
craniomaxillofacial (CMF) deformities. We have developed a LAndmark GEometric
Routine (LAGER), which automatically estimates a midsagittal plane for such
subjects. The LAGER algorithm was based on the assumption that the optimal
midsagittal plane ... | Calculating the Midsagittal Plane for Symmetrical Bilateral Shapes:
Applications to Clinical Facial Surgical Planning | 2,018 | http://arxiv.org/pdf/1803.05853v1 | Title Calculating Midsagittal Plane Symmetrical Bilateral Shapes Applications Clinical Facial Surgical Planning Summary difficult estimate midsagittal plane human subject craniomaxillofacial CMF deformity developed LAndmark GEometric Routine LAGER automatically estimate midsagittal plane subject LAGER algorithm based a... | [0.036003172397613525, -0.016190944239497185, -0.014704548753798008, -0.01214763056486845, -0.0763586163520813, 0.016911787912249565, 0.04265476390719414, 0.019419502466917038, -0.029951458796858788, -0.015894334763288498, 0.046580418944358826, -0.04820645600557327, 0.04766285791993141, 0.061788469552993774, -0.0097279... |
40,306 | 40,306 | ['Mark Buckler', 'Philip Bedoukian', 'Suren Jayasuriya', 'Adrian Sampson'] | 1803.06312v1 | Hardware support for deep convolutional neural networks (CNNs) is critical to
advanced computer vision in mobile and embedded devices. Current designs,
however, accelerate generic CNNs; they do not exploit the unique
characteristics of real-time vision. We propose to use the temporal redundancy
in natural video to avoi... | $EVA^2$ : Exploiting Temporal Redundancy in Live Computer Vision | 2,018 | http://arxiv.org/pdf/1803.06312v1 | Title EVA2 Exploiting Temporal Redundancy Live Computer Vision Summary Hardware support deep convolutional neural network CNNs critical advanced computer vision mobile embedded device Current design however accelerate generic CNNs exploit unique characteristic realtime vision propose use temporal redundancy natural vid... | [0.00023010426957625896, -0.013341701589524746, 0.009915933012962341, 0.04402770847082138, 0.011903786100447178, -0.00724615715444088, 0.025823159143328667, 0.020791269838809967, -0.08536995202302933, -0.009927554987370968, 0.0523238405585289, 0.031766269356012344, 0.025863926857709885, 0.06167365983128548, 0.017583893... |
40,307 | 40,307 | ['Santhosh Kelathodi Kumaran', 'Debi Prosad Dogra', 'Partha Pratim Roy'] | 1803.06480v1 | Accurate prediction of traffic signal duration for roadway junction is a
challenging problem due to the dynamic nature of traffic flows. Though
supervised learning can be used, parameters may vary across roadway junctions.
In this paper, we present a computer vision guided expert system that can learn
the departure rat... | Queuing Theory Guided Intelligent Traffic Scheduling through Video
Analysis using Dirichlet Process Mixture Model | 2,018 | http://arxiv.org/pdf/1803.06480v1 | Title Queuing Theory Guided Intelligent Traffic Scheduling Video Analysis using Dirichlet Process Mixture Model Summary Accurate prediction traffic signal duration roadway junction challenging problem due dynamic nature traffic flow Though supervised learning used parameter may vary across roadway junction paper presen... | [-0.02640136145055294, 0.03611454740166664, -0.024852652102708817, 0.015055868774652481, -0.021315794438123703, -0.009030913934111595, 0.04582371190190315, -0.007240314967930317, -0.07372841238975525, -0.006578462198376656, 0.06067094951868057, 0.017588892951607704, -0.0057592750526964664, 0.04473630338907242, 0.005372... |
40,308 | 40,308 | ['Krishnam Gupta', 'Syed Ashar Javed', 'Vineet Gandhi', 'K. Madhava Krishna'] | 1803.06508v1 | We present here, a novel network architecture called MergeNet for discovering
small obstacles for on-road scenes in the context of autonomous driving. The
basis of the architecture rests on the central consideration of training with
less amount of data since the physical setup and the annotation process for
small obsta... | MergeNet: A Deep Net Architecture for Small Obstacle Discovery | 2,018 | http://arxiv.org/pdf/1803.06508v1 | Title MergeNet Deep Net Architecture Small Obstacle Discovery Summary present novel network architecture called MergeNet discovering small obstacle onroad scene context autonomous driving basis architecture rest central consideration training le amount data since physical setup annotation process small obstacle hard sc... | [0.011626170948147774, -0.01305666845291853, -0.010674499906599522, 0.07377166301012039, 0.0040031601674854755, -0.013489176519215107, 0.03935679793357849, 0.0003020490985363722, 0.0035366166848689318, 0.023233594372868538, 0.07156191766262054, 0.034659434109926224, -0.007036035880446434, 0.010345452465116978, -0.01564... |
40,309 | 40,309 | ['Yuhang Wu', 'Le Anh Vu Ha', 'Xiang Xu', 'Ioannis A. Kakadiaris'] | 1803.06542v1 | We present a robust method for estimating the facial pose and shape
information from a densely annotated facial image. The method relies on
Convolutional Point-set Representation (CPR), a carefully designed matrix
representation to summarize different layers of information encoded in the set
of detected points in the a... | Convolutional Point-set Representation: A Convolutional Bridge Between a
Densely Annotated Image and 3D Face Alignment | 2,018 | http://arxiv.org/pdf/1803.06542v1 | Title Convolutional Pointset Representation Convolutional Bridge Densely Annotated Image 3D Face Alignment Summary present robust method estimating facial pose shape information densely annotated facial image method relies Convolutional Pointset Representation CPR carefully designed matrix representation summarize diff... | [-0.016604678705334663, 0.03491680696606636, 0.02134147845208645, 0.04443664848804474, 0.0006595528684556484, 0.03565140813589096, 0.02745899371802807, -0.019914060831069946, -0.03222307190299034, 0.05717878043651581, 0.021029969677329063, -0.003192090429365635, 0.04640021175146103, 0.05974411964416504, 0.0761551335453... |
40,310 | 40,310 | ['Fausto Milletari'] | 1803.06784v1 | Deep learning has been recently applied to a multitude of computer vision and
medical image analysis problems. Although recent research efforts have improved
the state of the art, most of the methods cannot be easily accessed, compared
or used by either researchers or the general public. Researchers often publish
their... | TOMAAT: volumetric medical image analysis as a cloud service | 2,018 | http://arxiv.org/pdf/1803.06784v1 | Title TOMAAT volumetric medical image analysis cloud service Summary Deep learning recently applied multitude computer vision medical image analysis problem Although recent research effort improved state art method cannot easily accessed compared used either researcher general public Researchers often publish code trai... | [0.013982894830405712, 0.02828451618552208, -0.03933200612664223, -0.0060801319777965546, -0.03505753353238106, 0.011235138401389122, 0.06309869885444641, 0.015698086470365524, -0.02105717733502388, 0.0611678846180439, 0.013749180361628532, -0.03666860982775688, -0.004285057075321674, 0.11884330213069916, -0.0072733103... |
40,311 | 40,311 | ['Ebrahim Karami', 'Mohamed Shehata', 'Andrew Smith'] | 1803.07195v1 | Detection of relative changes in circulating blood volume is important to
guide resuscitation and manage a variety of medical conditions including
sepsis, trauma, dialysis and congestive heart failure. Recent studies have
shown that estimates of circulating blood volume can be obtained from the
cross-sectional area (CS... | Adaptive Polar Active Contour for Segmentation and Tracking in
Ultrasound Videos | 2,018 | http://arxiv.org/pdf/1803.07195v1 | Title Adaptive Polar Active Contour Segmentation Tracking Ultrasound Videos Summary Detection relative change circulating blood volume important guide resuscitation manage variety medical condition including sepsis trauma dialysis congestive heart failure Recent study shown estimate circulating blood volume obtained cr... | [-0.018065381795167923, -0.046998780220746994, -0.004115324933081865, -0.021873291581869125, -0.030074240639805794, -0.018650222569704056, -0.0005764601519331336, 0.037784602493047714, -0.0801655724644661, 0.019680192694067955, 0.03762497752904892, -0.04529006779193878, 0.03816969692707062, 0.07727112621068954, -0.0257... |
40,312 | 40,312 | ['Diogo Martins', 'Kevin van Hecke', 'Guido de Croon'] | 1803.07512v1 | We study how autonomous robots can learn by themselves to improve their depth
estimation capability. In particular, we investigate a self-supervised learning
setup in which stereo vision depth estimates serve as targets for a
convolutional neural network (CNN) that transforms a single still image to a
dense depth map. ... | Fusion of stereo and still monocular depth estimates in a
self-supervised learning context | 2,018 | http://arxiv.org/pdf/1803.07512v1 | Title Fusion stereo still monocular depth estimate selfsupervised learning context Summary study autonomous robot learn improve depth estimation capability particular investigate selfsupervised learning setup stereo vision depth estimate serve target convolutional neural network CNN transforms single still image dense ... | [-0.010563453659415245, 0.034565072506666183, 0.04333442077040672, 0.06201520934700966, -0.02413177117705345, 0.0003617360780481249, 0.0007475299062207341, -0.07157953828573227, 0.00596252828836441, -0.01017394382506609, -0.008088960312306881, 0.08616618067026138, 0.0689392164349556, 0.07750210911035538, -0.00907636526... |
40,313 | 40,313 | ['Jahanzaib Shabbir', 'Tarique Anwer'] | 1803.07608v1 | Advancements in deep learning over the years have attracted research into how
deep artificial neural networks can be used in robotic systems. This research
survey will present a summarization of the current research with a specific
focus on the gains and obstacles for deep learning to be applied to mobile
robotics. | A Survey of Deep Learning Techniques for Mobile Robot Applications | 2,018 | http://arxiv.org/pdf/1803.07608v1 | Title Survey Deep Learning Techniques Mobile Robot Applications Summary Advancements deep learning year attracted research deep artificial neural network used robotic system research survey present summarization current research specific focus gain obstacle deep learning applied mobile robotics Authors 0 Ahmed Osman Wo... | [0.015231273137032986, -0.009188520722091198, 0.0069139264523983, -0.007576472125947475, 0.028974732384085655, -0.007769281510263681, 0.05428740382194519, -0.06158705800771713, -0.02860228531062603, 0.002343046711757779, -0.005057100672274828, 0.017214693129062653, 0.02101871557533741, 0.013576476834714413, 0.000271119... |
40,314 | 40,314 | ['Yao Feng', 'Fan Wu', 'Xiaohu Shao', 'Yanfeng Wang', 'Xi Zhou'] | 1803.07835v1 | We propose a straightforward method that simultaneously reconstructs the 3D
facial structure and provides dense alignment. To achieve this, we design a 2D
representation called UV position map which records the 3D shape of a complete
face in UV space, then train a simple Convolutional Neural Network to regress
it from ... | Joint 3D Face Reconstruction and Dense Alignment with Position Map
Regression Network | 2,018 | http://arxiv.org/pdf/1803.07835v1 | Title Joint 3D Face Reconstruction Dense Alignment Position Map Regression Network Summary propose straightforward method simultaneously reconstructs 3D facial structure provides dense alignment achieve design 2D representation called UV position map record 3D shape complete face UV space train simple Convolutional Neu... | [-0.008943664841353893, 0.08059017360210419, 0.032988306134939194, 0.03286537155508995, 0.017406389117240906, 0.01179974153637886, 0.041136227548122406, -0.055011238902807236, -0.014501125551760197, 0.05264900252223015, 0.016061274334788322, 0.006345445290207863, 0.041751496493816376, 0.05874032527208328, 0.07624429464... |
40,315 | 40,315 | ['He Zhang', 'Vishal M. Patel'] | 1803.08396v1 | We propose a new end-to-end single image dehazing method, called Densely
Connected Pyramid Dehazing Network (DCPDN), which can jointly learn the
transmission map, atmospheric light and dehazing all together. The end-to-end
learning is achieved by directly embedding the atmospheric scattering model
into the network, the... | Densely Connected Pyramid Dehazing Network | 2,018 | http://arxiv.org/pdf/1803.08396v1 | Title Densely Connected Pyramid Dehazing Network Summary propose new endtoend single image dehazing method called Densely Connected Pyramid Dehazing Network DCPDN jointly learn transmission map atmospheric light dehazing together endtoend learning achieved directly embedding atmospheric scattering model network thereby... | [-0.013162989169359207, 0.07105506956577301, 0.0255001001060009, 0.02561434730887413, -0.006126813590526581, -0.0012332377955317497, 0.04312821850180626, -0.03990963101387024, -0.03759907931089401, 0.02181920036673546, 0.005181949120014906, 0.018265308812260628, 0.002240333706140518, 0.04152150824666023, 0.005173272918... |
40,316 | 40,316 | ['Juan C. Cuevas-Tello', 'Peter Tino', 'Somak Raychaudhury'] | astro-ph/0605042v1 | We present a novel approach to estimate the time delay between light curves
of multiple images in a gravitationally lensed system, based on Kernel methods
in the context of machine learning. We perform various experiments with
artificially generated irregularly-sampled data sets to study the effect of the
various level... | How accurate are the time delay estimates in gravitational lensing? | 2,006 | http://arxiv.org/pdf/astro-ph/0605042v1 | Title accurate time delay estimate gravitational lensing Summary present novel approach estimate time delay light curve multiple image gravitationally lensed system based Kernel method context machine learning perform various experiment artificially generated irregularlysampled data set study effect various level noise... | [0.02268965356051922, 0.015392945148050785, 0.024316946044564247, 0.03565225005149841, -0.018530545756220818, -0.01876777783036232, 0.026120716705918312, 0.027575867250561714, -0.014050529338419437, 0.06961051374673843, 0.057929668575525284, -0.008745548315346241, 0.01161714643239975, 0.026085684075951576, 0.0037232290... |
40,317 | 40,317 | ['Carlos Domingo', 'Ricard Gavalda', 'Osamu Watanabe'] | cs/9809122v1 | One of the core applications of machine learning to knowledge discovery
consists on building a function (a hypothesis) from a given amount of data (for
instance a decision tree or a neural network) such that we can use it
afterwards to predict new instances of the data. In this paper, we focus on a
particular situation... | Practical algorithms for on-line sampling | 1,998 | http://arxiv.org/pdf/cs/9809122v1 | Title Practical algorithm online sampling Summary One core application machine learning knowledge discovery consists building function hypothesis given amount data instance decision tree neural network use afterwards predict new instance data paper focus particular situation assume hypothesis want use prediction simple... | [0.008534092456102371, 0.0005711129051633179, -0.04993244260549545, -0.05742217227816582, -0.05334196984767914, -0.05283227935433388, 0.020628461614251137, 0.008476627990603447, -0.0051377336494624615, -0.012482885271310806, 0.07790617644786835, 0.009044730104506016, -0.002951768459752202, 0.06664702296257019, 0.009462... |
40,318 | 40,318 | ['Jose M. Vidal', 'Edmund H. Durfee'] | cs/0001008v3 | We describe a framework and equations used to model and predict the behavior
of multi-agent systems (MASs) with learning agents. A difference equation is
used for calculating the progression of an agent's error in its decision
function, thereby telling us how the agent is expected to fare in the MAS. The
equation relie... | Predicting the expected behavior of agents that learn about agents: the
CLRI framework | 2,000 | http://arxiv.org/pdf/cs/0001008v3 | Title Predicting expected behavior agent learn agent CLRI framework Summary describe framework equation used model predict behavior multiagent system MASs learning agent difference equation used calculating progression agent error decision function thereby telling u agent expected fare MAS equation relies parameter cap... | [0.008230372332036495, 0.029347972944378853, -0.04035498946905136, -0.04027901962399483, -0.009558318182826042, -0.021262740716338158, 0.011407063342630863, -0.0008443869883194566, 0.023602569475769997, 0.016487136483192444, 0.04589390754699707, 0.08601026982069016, -0.03906124830245972, 0.11440533399581909, 0.00609103... |
40,319 | 40,319 | ['Jason W. H. Lee', 'Y. C. Tay', 'Anthony K. H. Tung'] | cs/0003072v1 | Ports, warehouses and courier services have to decide online how an arriving
task is to be served in order that cost is minimized (or profit maximized).
These operators have a wealth of historical data on task assignments; can these
data be mined for knowledge or rules that can help the decision-making?
MOO is a nove... | MOO: A Methodology for Online Optimization through Mining the Offline
Optimum | 2,000 | http://arxiv.org/pdf/cs/0003072v1 | Title MOO Methodology Online Optimization Mining Offline Optimum Summary Ports warehouse courier service decide online arriving task served order cost minimized profit maximized operator wealth historical data task assignment data mined knowledge rule help decisionmaking MOO novel application data mining online optimiz... | [0.006597134284675121, 0.03242281451821327, -0.045147404074668884, -0.02904730662703514, -0.036547139286994934, -0.04647543281316757, 0.029141418635845184, 0.013782457448542118, -0.02848721668124199, -0.03855440765619278, 0.03526497259736061, 0.017420554533600807, 0.010069633834064007, 0.09593798220157623, -0.026673033... |
40,320 | 40,320 | ['Myra Spiliopoulou', 'Carsten Pohle'] | cs/0008009v1 | For many companies, competitiveness in e-commerce requires a successful
presence on the web. Web sites are used to establish the company's image, to
promote and sell goods and to provide customer support. The success of a web
site affects and reflects directly the success of the company in the electronic
market. In thi... | Data Mining to Measure and Improve the Success of Web Sites | 2,000 | http://arxiv.org/pdf/cs/0008009v1 | Title Data Mining Measure Improve Success Web Sites Summary many company competitiveness ecommerce requires successful presence web Web site used establish company image promote sell good provide customer support success web site affect reflects directly success company electronic market study propose methodology impro... | [0.06181453540921211, 0.014684479683637619, -0.07342350482940674, 0.011562559753656387, -0.010182495228946209, -0.024648718535900116, -0.02752263844013214, -0.0009855584939941764, 0.010225930251181126, -0.05780337005853653, -0.008814605884253979, 0.03838764503598213, 0.012964402325451374, 0.0996888279914856, -0.0151398... |
40,321 | 40,321 | ['P. J. Costa Branco', 'J. A. Dente'] | cs/0010001v1 | Increasing demands in performance and quality make drive systems fundamental
parts in the progressive automation of industrial processes. Their conventional
models become inappropriate and have limited scope if one requires a precise
and fast performance. So, it is important to incorporate learning capabilities
into dr... | Design of an Electro-Hydraulic System Using Neuro-Fuzzy Techniques | 2,000 | http://arxiv.org/pdf/cs/0010001v1 | Title Design ElectroHydraulic System Using NeuroFuzzy Techniques Summary Increasing demand performance quality make drive system fundamental part progressive automation industrial process conventional model become inappropriate limited scope one requires precise fast performance important incorporate learning capabilit... | [0.0036828601732850075, -0.0109202666208148, -0.018785180523991585, 0.023349538445472717, 0.05917713791131973, -0.015431820414960384, 0.014251496642827988, 0.024445969611406326, 0.011630087159574032, -0.027539024129509926, -0.006260360591113567, 0.006125542335212231, -0.020345784723758698, 0.09915518015623093, 0.067255... |
40,322 | 40,322 | ['L. Henriques', 'L. Rolim', 'W. Suemitsu', 'P. J. Costa Branco', 'J. A. Dente'] | cs/0010003v1 | Simple power electronic drive circuit and fault tolerance of converter are
specific advantages of SRM drives, but excessive torque ripple has limited its
use to special applications. It is well known that controlling the current
shape adequately can minimize the torque ripple. This paper presents a new
method for shapi... | Torque Ripple Minimization in a Switched Reluctance Drive by Neuro-Fuzzy
Compensation | 2,000 | http://arxiv.org/pdf/cs/0010003v1 | Title Torque Ripple Minimization Switched Reluctance Drive NeuroFuzzy Compensation Summary Simple power electronic drive circuit fault tolerance converter specific advantage SRM drive excessive torque ripple limited use special application well known controlling current shape adequately minimize torque ripple paper pre... | [0.0012298135552555323, -0.0576154962182045, -0.007614586502313614, 0.03998211771249771, 0.06849004328250885, 0.03480752184987068, -0.040576815605163574, 0.044933732599020004, -0.026942884549498558, -0.018576832488179207, -0.07212325185537338, 0.05367274582386017, 0.03279720991849899, 0.0020183271262794733, 0.062968514... |
40,323 | 40,323 | ['P. J. Costa Branco', 'J. A. Dente'] | cs/0010004v1 | Fuzzy relational identification builds a relational model describing systems
behaviour by a nonlinear mapping between its variables. In this paper, we
propose a new fuzzy relational algorithm based on simplified max-min relational
equation. The algorithm presents an adaptation method applied to gravity-center
of each f... | A Fuzzy Relational Identification Algorithm and Its Application to
Predict The Behaviour of a Motor Drive System | 2,000 | http://arxiv.org/pdf/cs/0010004v1 | Title Fuzzy Relational Identification Algorithm Application Predict Behaviour Motor Drive System Summary Fuzzy relational identification build relational model describing system behaviour nonlinear mapping variable paper propose new fuzzy relational algorithm based simplified maxmin relational equation algorithm presen... | [0.002975630573928356, 0.01509788166731596, -0.037091244012117386, 0.04680187255144119, 0.05243018642067909, -0.012392891570925713, -0.013083777390420437, 0.06829347461462021, -0.03409520909190178, -0.04416867718100548, 0.04047213867306709, 0.020022481679916382, 0.016264067962765694, 0.02356390468776226, 0.018234666436... |
40,324 | 40,324 | ['Ron Kohavi', 'Foster Provost'] | cs/0010006v1 | Electronic commerce is emerging as the killer domain for data mining
technology.
The following are five desiderata for success. Seldom are they they all
present in one data mining application.
1. Data with rich descriptions. For example, wide customer records with many
potentially useful fields allow data mining al... | Applications of Data Mining to Electronic Commerce | 2,000 | http://arxiv.org/pdf/cs/0010006v1 | Title Applications Data Mining Electronic Commerce Summary Electronic commerce emerging killer domain data mining technology following five desideratum success Seldom present one data mining application 1 Data rich description example wide customer record many potentially useful field allow data mining algorithm search... | [0.02579558826982975, 0.02321487106382847, -0.07222168147563934, -0.03917626664042473, -0.006736941169947386, -0.016369720920920372, 0.025697611272335052, 0.02120760641992092, 0.012337983585894108, -0.04066060110926628, 0.052464984357357025, 0.05783417820930481, -0.0036351890303194523, 0.10627943277359009, -0.031227979... |
40,325 | 40,325 | ['J. F. Martins', 'P. J. Costa Branco', 'A. J. Pires', 'J. A. Dente'] | cs/0010010v1 | This paper describes two approaches for fault detection: an immune-based
mechanism and a formal language algorithm. The first one is based on the
feature of immune systems in distinguish any foreign cell from the body own
cell. The formal language approach assumes the system as a linguistic source
capable of generating... | Fault Detection using Immune-Based Systems and Formal Language
Algorithms | 2,000 | http://arxiv.org/pdf/cs/0010010v1 | Title Fault Detection using ImmuneBased Systems Formal Language Algorithms Summary paper describes two approach fault detection immunebased mechanism formal language algorithm first one based feature immune system distinguish foreign cell body cell formal language approach assumes system linguistic source capable gener... | [-0.004997967276722193, -0.005475686863064766, -0.004899755120277405, 0.040455710142850876, 0.014056321233510971, 0.0021785786375403404, -0.0013931437861174345, 0.041670769453048706, 0.027902251109480858, -0.03263649344444275, 0.03494080528616905, 0.06186250224709511, -0.0310117956250906, 0.021998563781380653, 0.027735... |
40,326 | 40,326 | ['Raymond Kosala', 'Hendrik Blockeel'] | cs/0011033v1 | With the huge amount of information available online, the World Wide Web is a
fertile area for data mining research. The Web mining research is at the cross
road of research from several research communities, such as database,
information retrieval, and within AI, especially the sub-areas of machine
learning and natura... | Web Mining Research: A Survey | 2,000 | http://arxiv.org/pdf/cs/0011033v1 | Title Web Mining Research Survey Summary huge amount information available online World Wide Web fertile area data mining research Web mining research cross road research several research community database information retrieval within AI especially subareas machine learning natural language processing However lot conf... | [0.05683673173189163, -0.020323069766163826, -0.05908024311065674, 0.02727709710597992, -0.03752746805548668, 0.004477543290704489, -0.011899896897375584, 0.04987180978059769, 0.0405898280441761, -0.06545339524745941, -0.019825389608740807, 0.017581287771463394, -0.02009870857000351, 0.03002067655324936, -0.03347265347... |
40,327 | 40,327 | ['Miklos Csuros', 'Ming-Yang Kao'] | cs/0011038v1 | We give a greedy learning algorithm for reconstructing an evolutionary tree
based on a certain harmonic average on triplets of terminal taxa. After the
pairwise distances between terminal taxa are estimated from sequence data, the
algorithm runs in O(n^2) time using O(n) work space, where n is the number of
terminal ta... | Provably Fast and Accurate Recovery of Evolutionary Trees through
Harmonic Greedy Triplets | 2,000 | http://arxiv.org/pdf/cs/0011038v1 | Title Provably Fast Accurate Recovery Evolutionary Trees Harmonic Greedy Triplets Summary give greedy learning algorithm reconstructing evolutionary tree based certain harmonic average triplet terminal taxon pairwise distance terminal taxon estimated sequence data algorithm run On2 time using work space n number termin... | [-0.00020817159384023398, 0.002156318398192525, -0.038919445127248764, 0.03292744606733322, -0.04822840169072151, -0.01921941339969635, -0.07306583970785141, 0.005469007417559624, -0.08651884645223618, -0.020765306428074837, 0.011013245210051537, -0.0183678288012743, 0.044046446681022644, -0.019971497356891632, -0.0066... |
40,328 | 40,328 | ['Leonid Peshkin', 'Kee-Eung Kim', 'Nicolas Meuleau', 'Leslie Pack Kaelbling'] | cs/0105032v1 | Cooperative games are those in which both agents share the same payoff
structure. Value-based reinforcement-learning algorithms, such as variants of
Q-learning, have been applied to learning cooperative games, but they only
apply when the game state is completely observable to both agents. Policy
search methods are a r... | Learning to Cooperate via Policy Search | 2,001 | http://arxiv.org/pdf/cs/0105032v1 | Title Learning Cooperate via Policy Search Summary Cooperative game agent share payoff structure Valuebased reinforcementlearning algorithm variant Qlearning applied learning cooperative game apply game state completely observable agent Policy search method reasonable alternative valuebased method partially observable ... | [0.020062007009983063, 0.017633290961384773, -0.006424515508115292, -0.025010263547301292, -0.019512081518769264, -0.029138581827282906, 0.013696065172553062, -0.012439778074622154, -0.05300769582390785, 0.026469215750694275, -0.023203184828162193, 0.034239478409290314, -0.029934445396065712, 0.05764662101864815, -0.01... |
40,329 | 40,329 | ['H. Zha', 'X. He', 'C. Ding', 'M. Gu', 'H. Simon'] | cs/0108018v1 | Many data types arising from data mining applications can be modeled as
bipartite graphs, examples include terms and documents in a text corpus,
customers and purchasing items in market basket analysis and reviewers and
movies in a movie recommender system. In this paper, we propose a new data
clustering method based o... | Bipartite graph partitioning and data clustering | 2,001 | http://arxiv.org/pdf/cs/0108018v1 | Title Bipartite graph partitioning data clustering Summary Many data type arising data mining application modeled bipartite graph example include term document text corpus customer purchasing item market basket analysis reviewer movie movie recommender system paper propose new data clustering method based partitioning ... | [-0.03341270610690117, -0.06608946621417999, -0.040868815034627914, 0.04267989844083786, -0.0008781430660746992, -0.0059021045453846455, 0.021489650011062622, 0.025868650525808334, 0.052667465060949326, -0.03636215627193451, -0.024478670209646225, 0.000952593341935426, 0.006679593585431576, 0.044751737266778946, -0.024... |
40,330 | 40,330 | ['Fabrizio Sebastiani'] | cs/0110053v1 | The automated categorization (or classification) of texts into predefined
categories has witnessed a booming interest in the last ten years, due to the
increased availability of documents in digital form and the ensuing need to
organize them. In the research community the dominant approach to this problem
is based on m... | Machine Learning in Automated Text Categorization | 2,001 | http://arxiv.org/pdf/cs/0110053v1 | Title Machine Learning Automated Text Categorization Summary automated categorization classification text predefined category witnessed booming interest last ten year due increased availability document digital form ensuing need organize research community dominant approach problem based machine learning technique gene... | [0.05879514664411545, 0.009347920306026936, -0.014472883194684982, 0.006601405330002308, -0.03558080643415451, 0.0383254699409008, 0.06159406900405884, 0.044500574469566345, 0.014392152428627014, -0.11289259046316147, 0.014665885828435421, 0.040010180324316025, -0.014747305773198605, 0.02154308557510376, -0.01890453509... |
40,331 | 40,331 | ['Igor Rivin'] | cs/0201009v1 | We analyze completely the convergence speed of the \emph{batch learning
algorithm}, and compare its speed to that of the memoryless learning algorithm
and of learning with memory. We show that the batch learning algorithm is never
worse than the memoryless learning algorithm (at least asymptotically). Its
performance \... | The performance of the batch learner algorithm | 2,002 | http://arxiv.org/pdf/cs/0201009v1 | Title performance batch learner algorithm Summary analyze completely convergence speed emphbatch learning algorithm compare speed memoryless learning algorithm learning memory show batch learning algorithm never worse memoryless learning algorithm least asymptotically performance emphvisavis learning full memory le cle... | [-0.02943568304181099, -0.015554862096905708, -0.00931650958955288, 0.03900032117962837, -0.02752218395471573, -0.007030193228274584, 0.010597363114356995, 0.0005834807525388896, 0.010417326353490353, -0.006062052678316832, 0.054371245205402374, 0.008599935099482536, 0.005579558666795492, 0.007584793027490377, 0.017838... |
40,332 | 40,332 | ['Bruno Caprile', 'Cesare Furlanello', 'Stefano Merler'] | cs/0201014v1 | The dynamical evolution of weights in the Adaboost algorithm contains useful
information about the role that the associated data points play in the built of
the Adaboost model. In particular, the dynamics induces a bipartition of the
data set into two (easy/hard) classes. Easy points are ininfluential in the
making of ... | The Dynamics of AdaBoost Weights Tells You What's Hard to Classify | 2,002 | http://arxiv.org/pdf/cs/0201014v1 | Title Dynamics AdaBoost Weights Tells Whats Hard Classify Summary dynamical evolution weight Adaboost algorithm contains useful information role associated data point play built Adaboost model particular dynamic induces bipartition data set two easyhard class Easy point ininfluential making model varying relevance hard... | [-0.058177921921014786, -0.022719861939549446, -0.057161714881658554, -0.021372245624661446, -0.029450057074427605, -0.030998390167951584, -0.007772929035127163, 0.012054900638759136, -0.040818266570568085, -0.03407305106520653, 0.05576731264591217, -0.0209879782050848, -0.026731785386800766, 0.024432964622974396, 0.01... |
40,333 | 40,333 | ['Philippe Jehiel', 'Dov Samet'] | cs/0201021v1 | A valuation for a player in a game in extensive form is an assignment of
numeric values to the players moves. The valuation reflects the desirability
moves. We assume a myopic player, who chooses a move with the highest
valuation. Valuations can also be revised, and hopefully improved, after each
play of the game. Here... | Learning to Play Games in Extensive Form by Valuation | 2,002 | http://arxiv.org/pdf/cs/0201021v1 | Title Learning Play Games Extensive Form Valuation Summary valuation player game extensive form assignment numeric value player move valuation reflects desirability move assume myopic player chooses move highest valuation Valuations also revised hopefully improved play game simple valuation revision considered move mad... | [0.017409658059477806, 0.02098689042031765, -0.033351682126522064, -0.005970817059278488, -0.03095303662121296, -0.03235180303454399, 0.009252902120351791, 0.002653855364769697, -0.017007987946271896, 0.027804285287857056, 0.01680121198296547, 0.04942906275391579, 0.003380248323082924, 0.07065777480602264, 0.0222332719... |
40,334 | 40,334 | ['L. Nunes', 'E. Oliveira'] | cs/0203010v1 | One of the main questions concerning learning in Multi-Agent Systems is:
(How) can agents benefit from mutual interaction during the learning process?.
This paper describes the study of an interactive advice-exchange mechanism as a
possible way to improve agents' learning performance. The advice-exchange
technique, dis... | On Learning by Exchanging Advice | 2,002 | http://arxiv.org/pdf/cs/0203010v1 | Title Learning Exchanging Advice Summary One main question concerning learning MultiAgent Systems agent benefit mutual interaction learning process paper describes study interactive adviceexchange mechanism possible way improve agent learning performance adviceexchange technique discussed us supervised learning backpro... | [0.04723718389868736, -0.027139032259583473, -0.0008920709951780736, -0.0024671920109540224, -0.029931610450148582, -0.020946316421031952, 0.04818824678659439, 0.036748748272657394, 0.021000536158680916, -0.04717952013015747, -0.05444607511162758, 0.06084440276026726, -0.01707993820309639, 0.03576262295246124, 0.002120... |
40,335 | 40,335 | ['S. E. Middleton', 'D. C. De Roure', 'N. R. Shadbolt'] | cs/0203011v1 | Tools for filtering the World Wide Web exist, but they are hampered by the
difficulty of capturing user preferences in such a dynamic environment. We
explore the acquisition of user profiles by unobtrusive monitoring of browsing
behaviour and application of supervised machine-learning techniques coupled
with an ontolog... | Capturing Knowledge of User Preferences: ontologies on recommender
systems | 2,002 | http://arxiv.org/pdf/cs/0203011v1 | Title Capturing Knowledge User Preferences ontology recommender system Summary Tools filtering World Wide Web exist hampered difficulty capturing user preference dynamic environment explore acquisition user profile unobtrusive monitoring browsing behaviour application supervised machinelearning technique coupled ontolo... | [0.019431253895163536, 0.003491645213216543, -0.021966971457004547, -0.018278710544109344, -0.005383140407502651, -0.030215958133339882, 0.011521953158080578, 0.023386197164654732, 0.018116489052772522, -0.05611789599061012, -0.02862335927784443, 0.05347994714975357, -0.011052615940570831, 0.08261500298976898, -0.05028... |
40,336 | 40,336 | ['Stuart E. Middleton'] | cs/0203012v1 | This paper reviews the origins of interface agents, discusses challenges that
exist within the interface agent field and presents a survey of current
attempts to find solutions to these challenges. A history of agent systems from
their birth in the 1960's to the current day is described, along with the
issues they try ... | Interface agents: A review of the field | 2,002 | http://arxiv.org/pdf/cs/0203012v1 | Title Interface agent review field Summary paper review origin interface agent discus challenge exist within interface agent field present survey current attempt find solution challenge history agent system birth 1960s current day described along issue try address taxonomy interface agent system presented today agent s... | [0.028566306456923485, -0.0024646723177284002, -0.029187966138124466, -0.04067528620362282, -0.022403543815016747, -0.014761436730623245, 0.12506458163261414, 0.018011460080742836, 0.029463784769177437, -0.08237533271312714, 0.022531501948833466, 0.03839288279414177, 0.0007424285286106169, 0.08298137784004211, -0.03063... |
40,337 | 40,337 | ['Stuart E. Middleton', 'Harith Alani', 'David C. De Roure'] | cs/0204012v1 | Recommender systems learn about user preferences over time, automatically
finding things of similar interest. This reduces the burden of creating
explicit queries. Recommender systems do, however, suffer from cold-start
problems where no initial information is available early on upon which to base
recommendations. Sema... | Exploiting Synergy Between Ontologies and Recommender Systems | 2,002 | http://arxiv.org/pdf/cs/0204012v1 | Title Exploiting Synergy Ontologies Recommender Systems Summary Recommender system learn user preference time automatically finding thing similar interest reduces burden creating explicit query Recommender system however suffer coldstart problem initial information available early upon base recommendation Semantic know... | [0.02213655784726143, -0.022221200168132782, -0.0025417006108909845, 0.031879719346761703, -0.02047674171626568, -0.013923279941082, 0.006422458216547966, 0.046167854219675064, 0.06322243064641953, -0.011015724390745163, -0.06281224638223648, 0.05839728191494942, -0.0037327203899621964, 0.03990672156214714, -0.04386232... |
40,338 | 40,338 | ['Pawel Wocjan', 'Dominik Janzing', 'Thomas Beth'] | cs/0204052v1 | Learning joint probability distributions on n random variables requires
exponential sample size in the generic case. Here we consider the case that a
temporal (or causal) order of the variables is known and that the (unknown)
graph of causal dependencies has bounded in-degree Delta. Then the joint
measure is uniquely d... | Required sample size for learning sparse Bayesian networks with many
variables | 2,002 | http://arxiv.org/pdf/cs/0204052v1 | Title Required sample size learning sparse Bayesian network many variable Summary Learning joint probability distribution n random variable requires exponential sample size generic case consider case temporal causal order variable known unknown graph causal dependency bounded indegree Delta joint measure uniquely deter... | [-0.07031698524951935, 0.042113207280635834, -0.0045181754976511, -0.038744110614061356, -0.024942999705672264, -0.03344540670514107, 0.014145727269351482, 0.004101193509995937, -0.0030284575186669827, 0.04297981411218643, 0.08729802817106247, 0.025675807148218155, -0.015458616428077221, 0.0758790448307991, 0.019703084... |
40,339 | 40,339 | ['Peter D. Turney'] | cs/0212011v1 | Keyphrases are useful for a variety of purposes, including summarizing,
indexing, labeling, categorizing, clustering, highlighting, browsing, and
searching. The task of automatic keyphrase extraction is to select keyphrases
from within the text of a given document. Automatic keyphrase extraction makes
it feasible to ge... | Mining the Web for Lexical Knowledge to Improve Keyphrase Extraction:
Learning from Labeled and Unlabeled Data | 2,002 | http://arxiv.org/pdf/cs/0212011v1 | Title Mining Web Lexical Knowledge Improve Keyphrase Extraction Learning Labeled Unlabeled Data Summary Keyphrases useful variety purpose including summarizing indexing labeling categorizing clustering highlighting browsing searching task automatic keyphrase extraction select keyphrases within text given document Autom... | [0.08669424802064896, 0.0004726031329482794, -0.0248882919549942, 0.01724308170378208, -0.03386417031288147, 0.020374882966279984, 0.007207467220723629, 0.04162249714136124, 0.042990054935216904, -0.08470093458890915, -0.03257684409618378, 0.02445419318974018, -0.03904176130890846, 0.040536265820264816, -0.032488875091... |
40,340 | 40,340 | ['Peter D. Turney', 'Michael L. Littman'] | cs/0212012v1 | The evaluative character of a word is called its semantic orientation. A
positive semantic orientation implies desirability (e.g., "honest", "intrepid")
and a negative semantic orientation implies undesirability (e.g., "disturbing",
"superfluous"). This paper introduces a simple algorithm for unsupervised
learning of s... | Unsupervised Learning of Semantic Orientation from a
Hundred-Billion-Word Corpus | 2,002 | http://arxiv.org/pdf/cs/0212012v1 | Title Unsupervised Learning Semantic Orientation HundredBillionWord Corpus Summary evaluative character word called semantic orientation positive semantic orientation implies desirability eg honest intrepid negative semantic orientation implies undesirability eg disturbing superfluous paper introduces simple algorithm ... | [0.03638465702533722, 0.04802272841334343, 0.012261605821549892, 0.034741371870040894, -0.056573085486888885, 0.005833770614117384, -0.018619144335389137, 0.009709101170301437, -0.027648236602544785, -0.08650469779968262, -0.025848999619483948, 0.014725024811923504, -0.03479154780507088, 0.005155219696462154, -0.046801... |
40,341 | 40,341 | ['Peter D. Turney'] | cs/0212013v1 | Many academic journals ask their authors to provide a list of about five to
fifteen key words, to appear on the first page of each article. Since these key
words are often phrases of two or more words, we prefer to call them
keyphrases. There is a surprisingly wide variety of tasks for which keyphrases
are useful, as w... | Learning to Extract Keyphrases from Text | 2,002 | http://arxiv.org/pdf/cs/0212013v1 | Title Learning Extract Keyphrases Text Summary Many academic journal ask author provide list five fifteen key word appear first page article Since key word often phrase two word prefer call keyphrases surprisingly wide variety task keyphrases useful discus paper Recent commercial software Microsofts Word 97 Veritys Sea... | [0.09169390052556992, 0.013856766745448112, 0.0009806343587115407, 0.01448131538927555, -0.07377471774816513, -0.0016155507182702422, -0.0015901315491646528, 0.059704750776290894, -0.014221765100955963, -0.08780954033136368, -0.0048411148600280285, 0.06281016021966934, -0.02416004240512848, 0.06910223513841629, -0.0097... |
40,342 | 40,342 | ['Peter D. Turney'] | cs/0212014v1 | This report presents an empirical evaluation of four algorithms for
automatically extracting keywords and keyphrases from documents. The four
algorithms are compared using five different collections of documents. For each
document, we have a target set of keyphrases, which were generated by hand. The
target keyphrases ... | Extraction of Keyphrases from Text: Evaluation of Four Algorithms | 2,002 | http://arxiv.org/pdf/cs/0212014v1 | Title Extraction Keyphrases Text Evaluation Four Algorithms Summary report present empirical evaluation four algorithm automatically extracting keywords keyphrases document four algorithm compared using five different collection document document target set keyphrases generated hand target keyphrases generated human re... | [0.10502571612596512, 0.02335081808269024, -0.007958398200571537, 0.03645702451467514, -0.06764131039381027, 0.011384225450456142, -0.013545306399464607, 0.03652391582727432, 0.014325404539704323, -0.036035891622304916, -0.004067026544362307, 0.04427414759993553, -0.009958134964108467, 0.03230181708931923, -0.025656249... |
40,343 | 40,343 | ['Paul Ginsparg', 'Paul Houle', 'Thorsten Joachims', 'Jae-Hoon Sul'] | cs/0312018v1 | We illustrate the use of machine learning techniques to analyze, structure,
maintain, and evolve a large online corpus of academic literature. An emerging
field of research can be identified as part of an existing corpus, permitting
the implementation of a more coherent community structure for its
practitioners. | Mapping Subsets of Scholarly Information | 2,003 | http://arxiv.org/pdf/cs/0312018v1 | Title Mapping Subsets Scholarly Information Summary illustrate use machine learning technique analyze structure maintain evolve large online corpus academic literature emerging field research identified part existing corpus permitting implementation coherent community structure practitioner Authors 0 Ahmed Osman Wojcie... | [0.07654443383216858, 0.027280297130346298, -0.01681380346417427, -0.030425678938627243, -0.02958918735384941, 0.014706148765981197, 0.06507299840450287, 0.0017690816894173622, -0.012238684110343456, -0.06364773958921432, 0.04124612733721733, 0.030261749401688576, 0.042241163551807404, 0.018805915489792824, 0.000575348... |
40,344 | 40,344 | ['Michael Engelhardt', 'Thomas C. Schmidt'] | cs/0408001v1 | The semantic Web initiates new, high level access schemes to online content
and applications. One area of superior need for a redefined content exploration
is given by on-line educational applications and their concepts of
interactivity in the framework of open hypermedia systems. In the present paper
we discuss aspect... | Semantic Linking - a Context-Based Approach to Interactivity in
Hypermedia | 2,004 | http://arxiv.org/pdf/cs/0408001v1 | Title Semantic Linking ContextBased Approach Interactivity Hypermedia Summary semantic Web initiate new high level access scheme online content application One area superior need redefined content exploration given online educational application concept interactivity framework open hypermedia system present paper discu... | [0.026540545746684074, -0.04479445517063141, -0.04275176674127579, 0.013507372699677944, 0.006416249554604292, -0.0005077125388197601, 0.05036525800824165, 0.02320271171629429, 0.01888970099389553, -0.07886579632759094, -0.03757977485656738, 0.05170177295804024, 0.013091139495372772, 0.05860414728522301, -2.79947053059... |
40,345 | 40,345 | ['Michael Engelhardt', 'Andreas Kárpáti', 'Torsten Rack', 'Ivette Schmidt', 'Thomas C. Schmidt'] | cs/0408004v1 | While eLearning systems become more and more popular in daily education,
available applications lack opportunities to structure, annotate and manage
their contents in a high-level fashion. General efforts to improve these
deficits are taken by initiatives to define rich meta data sets and a
semanticWeb layer. In the pr... | Hypermedia Learning Objects System - On the Way to a Semantic
Educational Web | 2,004 | http://arxiv.org/pdf/cs/0408004v1 | Title Hypermedia Learning Objects System Way Semantic Educational Web Summary eLearning system become popular daily education available application lack opportunity structure annotate manage content highlevel fashion General effort improve deficit taken initiative define rich meta data set semanticWeb layer present pap... | [0.0566190741956234, -0.06204478442668915, -0.02271381765604019, -0.014331642538309097, 0.029240557923913002, 0.008633237332105637, 0.060426902025938034, 0.01948327012360096, -0.007212317083030939, -0.05824689194560051, -0.047630324959754944, 0.05446719378232956, -0.03211446478962898, 0.05819861590862274, -0.0171304605... |
40,346 | 40,346 | ['Abraham D. Flaxman', 'Adam Tauman Kalai', 'H. Brendan McMahan'] | cs/0408007v1 | We consider a the general online convex optimization framework introduced by
Zinkevich. In this setting, there is a sequence of convex functions. Each
period, we must choose a signle point (from some feasible set) and pay a cost
equal to the value of the next function on our chosen point. Zinkevich shows
that, if the e... | Online convex optimization in the bandit setting: gradient descent
without a gradient | 2,004 | http://arxiv.org/pdf/cs/0408007v1 | Title Online convex optimization bandit setting gradient descent without gradient Summary consider general online convex optimization framework introduced Zinkevich setting sequence convex function period must choose signle point feasible set pay cost equal value next function chosen point Zinkevich show function revea... | [-0.002923975232988596, 0.07735494524240494, -0.00826902873814106, -0.039216455072164536, -0.012368648312985897, -0.019934285432100296, 0.007156228180974722, -0.0006864093011245131, -0.054359905421733856, 0.014889265410602093, 0.028479022905230522, 0.0350964292883873, -0.0285834688693285, 0.07376005500555038, 0.0226407... |
40,347 | 40,347 | ['John David Funge'] | cs/0408048v1 | This paper describes a new breed of academic journals that use statistical
machine learning techniques to make them more democratic. In particular, not
only can anyone submit an article, but anyone can also become a reviewer.
Machine learning is used to decide which reviewers accurately represent the
views of the journ... | Journal of New Democratic Methods: An Introduction | 2,004 | http://arxiv.org/pdf/cs/0408048v1 | Title Journal New Democratic Methods Introduction Summary paper describes new breed academic journal use statistical machine learning technique make democratic particular anyone submit article anyone also become reviewer Machine learning used decide reviewer accurately represent view journal reader thus deserve opinion... | [0.05107206851243973, 0.0735667496919632, -0.009622999466955662, -0.0719585195183754, -0.07784318178892136, 0.015032747760415077, 0.055869828909635544, 0.024727625772356987, -0.008748987689614296, -0.06324762105941772, 0.06926288455724716, 0.029328366741538048, -0.011794243939220905, 0.09144343435764313, -0.03549517318... |
40,348 | 40,348 | ['Daniil Ryabko'] | cs/0502074v2 | In statistical setting of the pattern recognition problem the number of
examples required to approximate an unknown labelling function is linear in the
VC dimension of the target learning class. In this work we consider the
question whether such bounds exist if we restrict our attention to computable
pattern recognitio... | On sample complexity for computational pattern recognition | 2,005 | http://arxiv.org/pdf/cs/0502074v2 | Title sample complexity computational pattern recognition Summary statistical setting pattern recognition problem number example required approximate unknown labelling function linear VC dimension target learning class work consider question whether bound exist restrict attention computable pattern recognition method a... | [0.021374402567744255, 0.017245087772607803, -0.026830071583390236, 0.032214365899562836, -0.03779323026537895, 0.002565982984378934, 0.019802020862698555, 0.01535489596426487, 0.012056774459779263, 0.012896411120891571, 0.06833449006080627, 0.04407091811299324, 0.05225135385990143, 0.0555502213537693, -0.0062507209368... |
40,349 | 40,349 | ['Zs. Palotai', 'Cs. Farkas', 'A. Lorincz'] | cs/0504063v1 | In this paper we compare the performance characteristics of our selection
based learning algorithm for Web crawlers with the characteristics of the
reinforcement learning algorithm. The task of the crawlers is to find new
information on the Web. The selection algorithm, called weblog update, modifies
the starting URL l... | Selection in Scale-Free Small World | 2,005 | http://arxiv.org/pdf/cs/0504063v1 | Title Selection ScaleFree Small World Summary paper compare performance characteristic selection based learning algorithm Web crawler characteristic reinforcement learning algorithm task crawler find new information Web selection algorithm called weblog update modifies starting URL list crawler based found URLs contain... | [0.04597756639122963, 0.005243521183729172, -0.02428816817700863, -0.029292726889252663, -0.04241345450282097, -0.027323095127940178, 0.057358503341674805, 0.0253529604524374, -0.0012008600169792771, -0.05304965376853943, -0.00024564992054365575, -0.005092862993478775, -0.018236855044960976, 0.07317128777503967, -0.007... |
40,350 | 40,350 | ['Erik M. Boczko', 'Todd R. Young'] | cs/0511105v1 | From a geometric perspective most nonlinear binary classification algorithms,
including state of the art versions of Support Vector Machine (SVM) and Radial
Basis Function Network (RBFN) classifiers, and are based on the idea of
reconstructing indicator functions. We propose instead to use reconstruction of
the signed ... | The Signed Distance Function: A New Tool for Binary Classification | 2,005 | http://arxiv.org/pdf/cs/0511105v1 | Title Signed Distance Function New Tool Binary Classification Summary geometric perspective nonlinear binary classification algorithm including state art version Support Vector Machine SVM Radial Basis Function Network RBFN classifier based idea reconstructing indicator function propose instead use reconstruction signe... | [-0.005632623098790646, -0.028795547783374786, -0.042892951518297195, 0.014851477928459644, -0.006530283018946648, 0.016990967094898224, 0.06747614592313766, 0.06764243543148041, 0.02340339682996273, -0.0037194713950157166, 0.07187700271606445, 0.04484649747610092, 0.03952674940228462, 0.06046967953443527, -0.009541356... |
40,351 | 40,351 | ['A. Benabdallah', 'G. Radons'] | cs/0511108v1 | We propose a new method for the estimation of parameters of hidden diffusion
processes. Based on parametrization of the transition matrix, the Baum-Welch
algorithm is improved. The algorithm is compared to the particle filter in
application to the noisy periodic systems. It is shown that the modified
Baum-Welch algorit... | Parameter Estimation of Hidden Diffusion Processes: Particle Filter vs.
Modified Baum-Welch Algorithm | 2,005 | http://arxiv.org/pdf/cs/0511108v1 | Title Parameter Estimation Hidden Diffusion Processes Particle Filter v Modified BaumWelch Algorithm Summary propose new method estimation parameter hidden diffusion process Based parametrization transition matrix BaumWelch algorithm improved algorithm compared particle filter application noisy periodic system shown mo... | [-0.015797868371009827, -0.0038131196051836014, -0.026773905381560326, 0.02131556160748005, 0.048977918922901154, -0.05646340176463127, 0.02028486877679825, 0.0066038439981639385, -0.03268333524465561, 0.0056676194071769714, 0.028461726382374763, 0.03026706352829933, 0.020479470491409302, 0.011083981022238731, -0.03705... |
40,352 | 40,352 | ['John M. Hitchcock'] | cs/0512053v1 | We establish a relationship between the online mistake-bound model of
learning and resource-bounded dimension. This connection is combined with the
Winnow algorithm to obtain new results about the density of hard sets under
adaptive reductions. This improves previous work of Fu (1995) and Lutz and Zhao
(2000), and solv... | Online Learning and Resource-Bounded Dimension: Winnow Yields New Lower
Bounds for Hard Sets | 2,005 | http://arxiv.org/pdf/cs/0512053v1 | Title Online Learning ResourceBounded Dimension Winnow Yields New Lower Bounds Hard Sets Summary establish relationship online mistakebound model learning resourcebounded dimension connection combined Winnow algorithm obtain new result density hard set adaptive reduction improves previous work Fu 1995 Lutz Zhao 2000 so... | [-0.06587023288011551, 0.04108745977282524, -0.018849078565835953, 0.027532454580068588, -0.01066253986209631, -0.01869548298418522, 0.010012760758399963, 0.019975734874606133, -0.05674705281853676, 0.014445040374994278, 0.05471170321106911, -0.032314546406269073, -0.03535313531756401, 0.05530862882733345, 0.0104511715... |
40,353 | 40,353 | ['Varsha Dani', 'Thomas P. Hayes'] | cs/0602053v1 | The multi-armed bandit is a concise model for the problem of iterated
decision-making under uncertainty. In each round, a gambler must pull one of
$K$ arms of a slot machine, without any foreknowledge of their payouts, except
that they are uniformly bounded. A standard objective is to minimize the
gambler's regret, def... | How to Beat the Adaptive Multi-Armed Bandit | 2,006 | http://arxiv.org/pdf/cs/0602053v1 | Title Beat Adaptive MultiArmed Bandit Summary multiarmed bandit concise model problem iterated decisionmaking uncertainty round gambler must pull one K arm slot machine without foreknowledge payouts except uniformly bounded standard objective minimize gambler regret defined gambler total payout minus largest payout wou... | [0.0014749632682651281, 0.054581139236688614, -0.014556560665369034, -0.03918652981519699, -0.010535583831369877, 0.006799404043704271, -0.02562343329191208, 0.03921663016080856, -0.008298059925436974, 0.00533329788595438, 0.010189703665673733, 0.04312364012002945, -0.04468678683042526, 0.04494569078087807, 0.025489652... |
40,354 | 40,354 | ['Viktor Zhumatiy', 'Faustino Gomez', 'Marcus Hutter', 'Juergen Schmidhuber'] | cs/0603023v1 | We address the problem of autonomously learning controllers for
vision-capable mobile robots. We extend McCallum's (1995) Nearest-Sequence
Memory algorithm to allow for general metrics over state-action trajectories.
We demonstrate the feasibility of our approach by successfully running our
algorithm on a real mobile r... | Metric State Space Reinforcement Learning for a Vision-Capable Mobile
Robot | 2,006 | http://arxiv.org/pdf/cs/0603023v1 | Title Metric State Space Reinforcement Learning VisionCapable Mobile Robot Summary address problem autonomously learning controller visioncapable mobile robot extend McCallums 1995 NearestSequence Memory algorithm allow general metric stateaction trajectory demonstrate feasibility approach successfully running algorith... | [-0.004157182760536671, -0.014268356375396252, -0.0049194591119885445, -0.03500690683722496, 0.010506812483072281, 0.008747166953980923, -0.008117609657347202, -0.021261554211378098, 0.01026320829987526, -0.028565583750605583, 0.023020097985863686, 0.04101480916142464, -0.022290745750069618, 0.0511169359087944, 0.00245... |
40,355 | 40,355 | ['Xenofontas Dimitropoulos', 'Dmitri Krioukov', 'George Riley', 'kc claffy'] | cs/0604015v1 | Although the Internet AS-level topology has been extensively studied over the
past few years, little is known about the details of the AS taxonomy. An AS
"node" can represent a wide variety of organizations, e.g., large ISP, or small
private business, university, with vastly different network characteristics,
external ... | Revealing the Autonomous System Taxonomy: The Machine Learning Approach | 2,006 | http://arxiv.org/pdf/cs/0604015v1 | Title Revealing Autonomous System Taxonomy Machine Learning Approach Summary Although Internet ASlevel topology extensively studied past year little known detail taxonomy node represent wide variety organization eg large ISP small private business university vastly different network characteristic external connectivity... | [-0.0008708498207852244, 0.0052917092107236385, -0.04262861609458923, -0.02005230076611042, -0.020449494943022728, -0.04235806688666344, 0.02963976189494133, -0.004164848476648331, 0.039302367717027664, -0.07338515669107437, 0.021300073713064194, 0.015453517436981201, -0.01184080820530653, 0.07130306959152222, 0.024789... |
40,356 | 40,356 | ['Vita Hinze-Hoare'] | cs/0604102v1 | The general set of HCI and Educational principles are considered and a
classification system constructed. A frequency analysis of principles is used
to obtain the most significant set. Metrics are devised to provide objective
measures of these principles and a consistent testing regime devised. These
principles are use... | HCI and Educational Metrics as Tools for VLE Evaluation | 2,006 | http://arxiv.org/pdf/cs/0604102v1 | Title HCI Educational Metrics Tools VLE Evaluation Summary general set HCI Educational principle considered classification system constructed frequency analysis principle used obtain significant set Metrics devised provide objective measure principle consistent testing regime devised principle used analyse Blackboard M... | [-0.033492956310510635, 0.0017637767596170306, -0.0654880553483963, -0.018694251775741577, -0.020220240578055382, -0.006769230589270592, 0.07385764271020889, 0.003916100598871708, -0.026680639013648033, -0.006607159972190857, 0.024157000705599785, -0.008362531661987305, 0.06294704228639603, 0.031193634495139122, -0.048... |
40,357 | 40,357 | ['Filip Radlinski', 'Thorsten Joachims'] | cs/0605035v1 | This paper presents a novel approach for using clickthrough data to learn
ranked retrieval functions for web search results. We observe that users
searching the web often perform a sequence, or chain, of queries with a similar
information need. Using query chains, we generate new types of preference
judgments from sear... | Query Chains: Learning to Rank from Implicit Feedback | 2,006 | http://arxiv.org/pdf/cs/0605035v1 | Title Query Chains Learning Rank Implicit Feedback Summary paper present novel approach using clickthrough data learn ranked retrieval function web search result observe user searching web often perform sequence chain query similar information need Using query chain generate new type preference judgment search engine l... | [0.04862530529499054, 0.027563845738768578, -0.009766959585249424, -0.014562874101102352, 0.005913798231631517, -0.015355034731328487, -0.0011939278338104486, 0.026669878512620926, 0.02551320008933544, -0.07067506015300751, -0.06569186598062515, 0.019249100238084793, -0.034412071108818054, 0.03219762071967125, 0.013837... |
40,358 | 40,358 | ['Filip Radlinski', 'Thorsten Joachims'] | cs/0605036v1 | This paper evaluates the robustness of learning from implicit feedback in web
search. In particular, we create a model of user behavior by drawing upon user
studies in laboratory and real-world settings. The model is used to understand
the effect of user behavior on the performance of a learning algorithm for
ranked re... | Evaluating the Robustness of Learning from Implicit Feedback | 2,006 | http://arxiv.org/pdf/cs/0605036v1 | Title Evaluating Robustness Learning Implicit Feedback Summary paper evaluates robustness learning implicit feedback web search particular create model user behavior drawing upon user study laboratory realworld setting model used understand effect user behavior performance learning algorithm ranked retrieval explore wi... | [0.043348293751478195, 0.008333842270076275, -0.038929250091314316, 0.0094949034973979, 0.02802620641887188, -0.02157623879611492, 0.015016879886388779, 0.048722170293331146, 0.057492662221193314, -0.07121572643518448, -0.03918406367301941, 0.03453163057565689, -0.038217172026634216, 0.04639019817113876, 0.024851141497... |
40,359 | 40,359 | ['Filip Radlinski', 'Thorsten Joachims'] | cs/0605037v1 | Clickthrough data is a particularly inexpensive and plentiful resource to
obtain implicit relevance feedback for improving and personalizing search
engines. However, it is well known that the probability of a user clicking on a
result is strongly biased toward documents presented higher in the result set
irrespective o... | Minimally Invasive Randomization for Collecting Unbiased Preferences
from Clickthrough Logs | 2,006 | http://arxiv.org/pdf/cs/0605037v1 | Title Minimally Invasive Randomization Collecting Unbiased Preferences Clickthrough Logs Summary Clickthrough data particularly inexpensive plentiful resource obtain implicit relevance feedback improving personalizing search engine However well known probability user clicking result strongly biased toward document pres... | [0.05254470184445381, 0.04124430567026138, -0.01157377753406763, -0.02979978919029236, -0.022037863731384277, -0.03351684659719467, 0.040634315460920334, 0.00392712838947773, 0.02387697622179985, -0.05854501947760582, -0.04156970605254173, 0.06392809003591537, -0.005811878014355898, 0.033671893179416656, 0.009384103119... |
40,360 | 40,360 | ['Marco Cuturi'] | cs/0606100v4 | This paper has been withdrawn by the author due to a crucial error in the
proof of Lemma 5. | The generating function of the polytope of transport matrices $U(r,c)$
as a positive semidefinite kernel of the marginals $r$ and $c$ | 2,006 | http://arxiv.org/pdf/cs/0606100v4 | Title generating function polytope transport matrix Urc positive semidefinite kernel marginals r c Summary paper withdrawn author due crucial error proof Lemma 5 Authors 0 Ahmed Osman Wojciech Samek 1 Ji Young Lee Franck Dernoncourt 2 Iulian Vlad Serban Tim Klinger Gerald Tesau 3 Sebastian Ruder Joachim Bingel Isabelle... | [-0.050464581698179245, -0.035031624138355255, -0.04839630424976349, 0.026818327605724335, -0.009198560379445553, -0.02577589824795723, 0.018148157745599747, -0.03167515620589256, -0.05279622599482536, -0.020615188404917717, 0.04895365983247757, -0.006830999627709389, -0.012124580331146717, 0.0743354856967926, 0.048846... |
40,361 | 40,361 | ['Baris E. Perk', 'J. J. E. Slotine'] | cs/0609140v2 | We introduce a simple framework for learning aggressive maneuvers in flight
control of UAVs. Having inspired from biological environment, dynamic movement
primitives are analyzed and extended using nonlinear contraction theory.
Accordingly, primitives of an observed movement are stably combined and
concatenated. We dem... | Motion Primitives for Robotic Flight Control | 2,006 | http://arxiv.org/pdf/cs/0609140v2 | Title Motion Primitives Robotic Flight Control Summary introduce simple framework learning aggressive maneuver flight control UAVs inspired biological environment dynamic movement primitive analyzed extended using nonlinear contraction theory Accordingly primitive observed movement stably combined concatenated demonstr... | [0.035495657473802567, -0.02553706057369709, 0.028295304626226425, -0.08461514115333557, -0.018910972401499748, -0.018877577036619186, -0.03975630924105644, 0.015976106747984886, -0.05602546036243439, -0.03914618864655495, -0.001758318510837853, 0.007463730406016111, 0.014064645394682884, 0.04633177071809769, 0.0247267... |
40,362 | 40,362 | ['Pavel Dmitriev', 'Carl Lagoze'] | cs/0609153v1 | There has been a lot of recent interest in mining patterns from graphs.
Often, the exact structure of the patterns of interest is not known. This
happens, for example, when molecular structures are mined to discover fragments
useful as features in chemical compound classification task, or when web sites
are mined to di... | Mining Generalized Graph Patterns based on User Examples | 2,006 | http://arxiv.org/pdf/cs/0609153v1 | Title Mining Generalized Graph Patterns based User Examples Summary lot recent interest mining pattern graph Often exact structure pattern interest known happens example molecular structure mined discover fragment useful feature chemical compound classification task web site mined discover set web page representing log... | [0.06627093255519867, 0.014627905562520027, -0.024359960108995438, 0.015465334057807922, -0.03030496835708618, -0.018758943304419518, -0.0319567508995533, 0.03803868964314461, 0.039396196603775024, -0.005857040639966726, 0.02589755319058895, 0.008256863802671432, -0.006022629793733358, 0.08424750715494156, 0.0051613426... |
40,363 | 40,363 | ['Tony T. Lee', 'Tong Ye'] | cs/0611024v1 | Functional decomposition of logic circuits has profound influence on all
quality aspects of the cost-effective implementation of modern digital systems.
In this paper, a relational approach to the decomposition of logic circuits is
proposed. This approach is parallel to the normalization of relational
databases, they a... | A Relational Approach to Functional Decomposition of Logic Circuits | 2,006 | http://arxiv.org/pdf/cs/0611024v1 | Title Relational Approach Functional Decomposition Logic Circuits Summary Functional decomposition logic circuit profound influence quality aspect costeffective implementation modern digital system paper relational approach decomposition logic circuit proposed approach parallel normalization relational database governe... | [-0.030064251273870468, 0.009287094697356224, -0.04569679871201515, 0.018017461523413658, -0.06434564292430878, -0.05583547428250313, 0.03947028890252113, -0.007060387637466192, 0.08106929808855057, -0.017374157905578613, -0.006256432738155127, 0.06742461770772934, -0.027897583320736885, 0.08947733789682388, -0.0506679... |
40,364 | 40,364 | ['Vita Hinze-Hoare'] | cs/0611042v1 | It is suggested that a new area of CSCR (Computer Supported Collaborative
Research) is distinguished from CSCW and CSCL and that the demarcation between
the three areas could do with greater clarification and prescription. | CSCR:Computer Supported Collaborative Research | 2,006 | http://arxiv.org/pdf/cs/0611042v1 | Title CSCRComputer Supported Collaborative Research Summary suggested new area CSCR Computer Supported Collaborative Research distinguished CSCW CSCL demarcation three area could greater clarification prescription Authors 0 Ahmed Osman Wojciech Samek 1 Ji Young Lee Franck Dernoncourt 2 Iulian Vlad Serban Tim Klinger Ge... | [0.04730018228292465, 0.01421235129237175, -0.029759839177131653, -0.015118471346795559, -0.060485512018203735, 0.01642431877553463, 0.08498480170965195, 0.005907594691962004, -0.022727280855178833, -0.005583982914686203, 0.03884219378232956, -0.012415231205523014, 0.08079066127538681, 0.015275266952812672, 3.565641236... |
40,365 | 40,365 | ['Remko Troncon', 'Gerda Janssens'] | cs/0701105v1 | Because query execution is the most crucial part of Inductive Logic
Programming (ILP) algorithms, a lot of effort is invested in developing faster
execution mechanisms. These execution mechanisms typically have a low-level
implementation, making them hard to debug. Moreover, other factors such as the
complexity of the ... | A Delta Debugger for ILP Query Execution | 2,007 | http://arxiv.org/pdf/cs/0701105v1 | Title Delta Debugger ILP Query Execution Summary query execution crucial part Inductive Logic Programming ILP algorithm lot effort invested developing faster execution mechanism execution mechanism typically lowlevel implementation making hard debug Moreover factor complexity problem handled ILP algorithm size code bas... | [-0.017243051901459694, 0.05093931779265404, -0.034854955971241, 0.004644762724637985, -0.021053772419691086, -0.011590993963181973, -0.03665784001350403, 0.049084845930337906, 0.033566899597644806, -0.023245833814144135, 0.0704963281750679, 0.08979319036006927, 0.015396964736282825, 0.020031683146953583, -0.0320613719... |
40,366 | 40,366 | ['Pirkko Kuusela', 'Daniel Ocone', 'Eduardo D. Sontag'] | math/0012163v2 | This paper takes a computational learning theory approach to a problem of
linear systems identification. It is assumed that input signals have only a
finite number k of frequency components, and systems to be identified have
dimension no greater than n. The main result establishes that the sample
complexity needed for ... | Learning Complexity Dimensions for a Continuous-Time Control System | 2,000 | http://arxiv.org/pdf/math/0012163v2 | Title Learning Complexity Dimensions ContinuousTime Control System Summary paper take computational learning theory approach problem linear system identification assumed input signal finite number k frequency component system identified dimension greater n main result establishes sample complexity needed identification... | [-0.06769251823425293, -0.021872879937291145, -0.022675802931189537, 0.027106238529086113, 0.003302662866190076, 0.004121529869735241, 0.025250375270843506, 0.014044385403394699, 0.03112214431166649, 0.043189141899347305, 0.060750849545001984, 0.016137922182679176, -0.012143895030021667, 0.07140233367681503, 0.01238597... |
40,367 | 40,367 | ['Andreas U. Schmidt'] | nlin/0306055v2 | Based on the heuristics that maintaining presumptions can be beneficial in
uncertain environments, we propose a set of basic axioms for learning systems
to incorporate the concept of prejudice. The simplest, memoryless model of a
deterministic learning rule obeying the axioms is constructed, and shown to be
equivalent ... | A Model for Prejudiced Learning in Noisy Environments | 2,003 | http://arxiv.org/pdf/nlin/0306055v2 | Title Model Prejudiced Learning Noisy Environments Summary Based heuristic maintaining presumption beneficial uncertain environment propose set basic axiom learning system incorporate concept prejudice simplest memoryless model deterministic learning rule obeying axiom constructed shown equivalent logistic map system p... | [-0.03045649081468582, 0.013395663350820541, -0.017827216535806656, -0.025856567546725273, 0.0061282687820494175, 0.014987383969128132, 0.00038831925485283136, -0.017935017123818398, 0.04500409588217735, 0.0029105201829224825, 0.033079445362091064, 0.002064928412437439, -0.024852709844708443, 0.015382681041955948, 0.00... |
40,368 | 40,368 | ['Rami Kanhouche'] | nlin/0511015v1 | We present a perceptional mathematical model for image and signal analysis. A
resemblance measure is defined, and submitted to an innovating combinatorial
optimization algorithm. Numerical Simulations are also presented | Combinatorial Approach to Object Analysis | 2,005 | http://arxiv.org/pdf/nlin/0511015v1 | Title Combinatorial Approach Object Analysis Summary present perceptional mathematical model image signal analysis resemblance measure defined submitted innovating combinatorial optimization algorithm Numerical Simulations also presented Authors 0 Ahmed Osman Wojciech Samek 1 Ji Young Lee Franck Dernoncourt 2 Iulian Vl... | [0.011608930304646492, -0.000545590475667268, -0.021707871928811073, 0.07762917876243591, -0.05203389748930931, 0.019260458648204803, 0.02246069349348545, 0.0631515309214592, -0.04364767670631409, -0.019521096721291542, -0.013816926628351212, -0.02670856937766075, 0.03368411958217621, -0.012329029850661755, -0.00272354... |
40,369 | 40,369 | ['Jean-Philippe Vert', 'Jian Qiu', 'William Stafford Noble'] | q-bio/0610040v1 | Much recent work in bioinformatics has focused on the inference of various
types of biological networks, representing gene regulation, metabolic
processes, protein-protein interactions, etc. A common setting involves
inferring network edges in a supervised fashion from a set of high-confidence
edges, possibly character... | Metric learning pairwise kernel for graph inference | 2,006 | http://arxiv.org/pdf/q-bio/0610040v1 | Title Metric learning pairwise kernel graph inference Summary Much recent work bioinformatics focused inference various type biological network representing gene regulation metabolic process proteinprotein interaction etc common setting involves inferring network edge supervised fashion set highconfidence edge possibly... | [-0.0338900126516819, 0.007867829874157906, -0.025378555059432983, 0.003370140213519335, -0.01586868427693844, -0.018755795434117317, 0.021442893892526627, 0.05805424600839615, 0.0610395222902298, 0.004342387430369854, 0.02946946769952774, 0.056389451026916504, 0.0015114106936380267, 0.05656930431723595, 0.028753481805... |
40,370 | 40,370 | ['Alp Atici', 'Rocco A. Servedio'] | quant-ph/0411140v2 | In this article we give several new results on the complexity of algorithms
that learn Boolean functions from quantum queries and quantum examples.
Hunziker et al. conjectured that for any class C of Boolean functions, the
number of quantum black-box queries which are required to exactly identify an
unknown function ... | Improved Bounds on Quantum Learning Algorithms | 2,004 | http://arxiv.org/pdf/quant-ph/0411140v2 | Title Improved Bounds Quantum Learning Algorithms Summary article give several new result complexity algorithm learn Boolean function quantum query quantum example Hunziker et al conjectured class C Boolean function number quantum blackbox query required exactly identify unknown function C Ofraclog CsqrthatgammaC hatga... | [-0.053530823439359665, 0.02636893279850483, -0.027615264058113098, 0.024225784465670586, -0.05119882524013519, -0.02163315936923027, -0.03183305263519287, 0.035785235464572906, 0.012759746983647346, -0.010025491937994957, 0.006887285970151424, 0.0002472365740686655, -0.04071148484945297, 0.046156853437423706, 0.007289... |
40,371 | 40,371 | ['Hideto Utsumi', 'Seiji Miyoshi', 'Masato Okada'] | 0705.2318v1 | We analyze the generalization performance of a student in a model composed of
nonlinear perceptrons: a true teacher, ensemble teachers, and the student. We
calculate the generalization error of the student analytically or numerically
using statistical mechanics in the framework of on-line learning. We treat two
well-kn... | Statistical Mechanics of Nonlinear On-line Learning for Ensemble
Teachers | 2,007 | http://arxiv.org/pdf/0705.2318v1 | Title Statistical Mechanics Nonlinear Online Learning Ensemble Teachers Summary analyze generalization performance student model composed nonlinear perceptrons true teacher ensemble teacher student calculate generalization error student analytically numerically using statistical mechanic framework online learning treat... | [-0.017756173387169838, -0.005308047402650118, -0.04543326422572136, 0.009822359308600426, 0.0019986785482615232, -0.015890099108219147, 0.008761576376855373, -0.015275483019649982, -0.037508197128772736, -0.0008207200444303453, 0.021659642457962036, 0.007325401529669762, -0.01074306946247816, 0.0310962051153183, 0.028... |
40,372 | 40,372 | ['Alp Atici', 'Rocco A. Servedio'] | 0707.3479v1 | In this article we develop quantum algorithms for learning and testing
juntas, i.e. Boolean functions which depend only on an unknown set of k out of
n input variables. Our aim is to develop efficient algorithms:
- whose sample complexity has no dependence on n, the dimension of the domain
the Boolean functions are d... | Quantum Algorithms for Learning and Testing Juntas | 2,007 | http://arxiv.org/pdf/0707.3479v1 | Title Quantum Algorithms Learning Testing Juntas Summary article develop quantum algorithm learning testing junta ie Boolean function depend unknown set k n input variable aim develop efficient algorithm whose sample complexity dependence n dimension domain Boolean function defined access classical quantum membership b... | [-0.04843463376164436, 0.04549448937177658, -0.060376886278390884, 0.009253391064703465, -0.06872299313545227, -0.021575290709733963, -0.021291209384799004, 0.05462893098592758, 0.018366502597928047, -0.013052599504590034, 0.017544180154800415, 0.009166756644845009, -0.003633859334513545, 0.012620922178030014, -0.00464... |
40,373 | 40,373 | ['Pierre Mahé', 'Jean-Philippe Vert'] | 0708.0171v1 | Support vector machines and kernel methods have recently gained considerable
attention in chemoinformatics. They offer generally good performance for
problems of supervised classification or regression, and provide a flexible and
computationally efficient framework to include relevant information and prior
knowledge ab... | Virtual screening with support vector machines and structure kernels | 2,007 | http://arxiv.org/pdf/0708.0171v1 | Title Virtual screening support vector machine structure kernel Summary Support vector machine kernel method recently gained considerable attention chemoinformatics offer generally good performance problem supervised classification regression provide flexible computationally efficient framework include relevant informa... | [0.016962455585598946, -0.06650014966726303, -0.03220294043421745, 0.004308056551963091, 0.023664701730012894, 0.007916932925581932, 0.030313054099678993, 0.036355629563331604, 0.03559771925210953, 0.00960541982203722, 0.05082330107688904, 0.009387184865772724, -0.020388957113027573, 0.03548260033130646, 0.048311382532... |
40,374 | 40,374 | ['Rustem Takhanov'] | 0708.3226v7 | In the constraint satisfaction problem ($CSP$), the aim is to find an
assignment of values to a set of variables subject to specified constraints. In
the minimum cost homomorphism problem ($MinHom$), one is additionally given
weights $c_{va}$ for every variable $v$ and value $a$, and the aim is to find
an assignment $f... | A Dichotomy Theorem for General Minimum Cost Homomorphism Problem | 2,007 | http://arxiv.org/pdf/0708.3226v7 | Title Dichotomy Theorem General Minimum Cost Homomorphism Problem Summary constraint satisfaction problem CSP aim find assignment value set variable subject specified constraint minimum cost homomorphism problem MinHom one additionally given weight cva every variable v value aim find assignment f variable minimizes sum... | [-0.030050046741962433, 0.016640648245811462, 0.003928770311176777, -0.00855050329118967, -0.06164659187197685, -0.03819020465016365, 0.01520606316626072, 0.008697858080267906, 0.03600591793656349, 0.03662881255149841, -0.007128934841603041, 0.08891448378562927, 0.0029243475291877985, -0.023487459868192673, 0.020082233... |
40,375 | 40,375 | ['Henryk Gzyl', 'Enrique ter Horst'] | 0709.0509v1 | The purpose of this note is to show how the method of maximum entropy in the
mean (MEM) may be used to improve parametric estimation when the measurements
are corrupted by large level of noise. The method is developed in the context
on a concrete example: that of estimation of the parameter in an exponential
distributi... | Filtering Additive Measurement Noise with Maximum Entropy in the Mean | 2,007 | http://arxiv.org/pdf/0709.0509v1 | Title Filtering Additive Measurement Noise Maximum Entropy Mean Summary purpose note show method maximum entropy mean MEM may used improve parametric estimation measurement corrupted large level noise method developed context concrete example estimation parameter exponential distribution compare performance method baye... | [-0.052881717681884766, -0.043170709162950516, 0.005870555527508259, -0.015224654227495193, 0.017821211367845535, -0.03630654141306877, -0.012563824653625488, 0.014525740407407284, -0.035580746829509735, 0.01129065454006195, 0.015135345049202442, -0.023182986304163933, 0.06846415996551514, 0.004468476865440607, 0.00267... |
40,376 | 40,376 | ['Fangwen Fu', 'Mihaela van der Schaar'] | 0709.2446v1 | In this paper, we model the various wireless users in a cognitive radio
network as a collection of selfish, autonomous agents that strategically
interact in order to acquire the dynamically available spectrum opportunities.
Our main focus is on developing solutions for wireless users to successfully
compete with each o... | Learning for Dynamic Bidding in Cognitive Radio Resources | 2,007 | http://arxiv.org/pdf/0709.2446v1 | Title Learning Dynamic Bidding Cognitive Radio Resources Summary paper model various wireless user cognitive radio network collection selfish autonomous agent strategically interact order acquire dynamically available spectrum opportunity main focus developing solution wireless user successfully compete limited timevar... | [0.0305547583848238, -0.02782287821173668, -0.017847683280706406, -0.08480095863342285, -0.020675944164395332, -0.03320019692182541, -0.03379562124609947, -0.05334581062197685, -0.028098171576857567, -0.013167893514037132, 0.004132991656661034, 0.04383956640958786, -0.01529625803232193, 0.01997312903404236, -0.01851548... |
40,377 | 40,377 | ['Fabrice Rossi', 'Damien François', 'Vincent Wertz', 'Marc Meurens', 'Michel Verleysen'] | 0709.3639v1 | The large number of spectral variables in most data sets encountered in
spectral chemometrics often renders the prediction of a dependent variable
uneasy. The number of variables hopefully can be reduced, by using either
projection techniques or selection methods; the latter allow for the
interpretation of the selected... | Fast Selection of Spectral Variables with B-Spline Compression | 2,007 | http://arxiv.org/pdf/0709.3639v1 | Title Fast Selection Spectral Variables BSpline Compression Summary large number spectral variable data set encountered spectral chemometrics often render prediction dependent variable uneasy number variable hopefully reduced using either projection technique selection method latter allow interpretation selected variab... | [0.015580626204609871, 0.01898857019841671, -0.03956709802150726, -0.0025992360897362232, 0.005113834515213966, -0.018174858763813972, 0.03385493904352188, 0.03370346873998642, 0.032063961029052734, 0.010204726830124855, -0.0024048995692282915, 0.056809406727552414, 0.008868793956935406, 0.023831434547901154, -0.000181... |
40,378 | 40,378 | ['Damien François', 'Fabrice Rossi', 'Vincent Wertz', 'Michel Verleysen'] | 0709.3640v1 | Combining the mutual information criterion with a forward feature selection
strategy offers a good trade-off between optimality of the selected feature
subset and computation time. However, it requires to set the parameter(s) of
the mutual information estimator and to determine when to halt the forward
procedure. These... | Resampling methods for parameter-free and robust feature selection with
mutual information | 2,007 | http://arxiv.org/pdf/0709.3640v1 | Title Resampling method parameterfree robust feature selection mutual information Summary Combining mutual information criterion forward feature selection strategy offer good tradeoff optimality selected feature subset computation time However requires set parameter mutual information estimator determine halt forward p... | [-0.0671466588973999, -0.010266963392496109, -0.023261653259396553, -0.0023358757607638836, -0.015412699431180954, -0.0008786776452325284, 0.04412262886762619, 0.033949170261621475, 0.02701445296406746, -0.024591609835624695, 0.01817939803004265, 0.03687065839767456, 0.018265653401613235, 0.023471765220165253, 0.005886... |
40,379 | 40,379 | ['Leonid', 'Kontorovich'] | 0712.0840v1 | We give a universal kernel that renders all the regular languages linearly
separable. We are not able to compute this kernel efficiently and conjecture
that it is intractable, but we do have an efficient $\eps$-approximation. | A Universal Kernel for Learning Regular Languages | 2,007 | http://arxiv.org/pdf/0712.0840v1 | Title Universal Kernel Learning Regular Languages Summary give universal kernel render regular language linearly separable able compute kernel efficiently conjecture intractable efficient epsapproximation Authors 0 Ahmed Osman Wojciech Samek 1 Ji Young Lee Franck Dernoncourt 2 Iulian Vlad Serban Tim Klinger Gerald Tesa... | [0.004468618892133236, 0.03407047688961029, -0.014084525406360626, 0.0772283747792244, -0.010636849328875542, -0.005167805589735508, -0.021650521084666252, 0.04043545573949814, -0.010719165205955505, 0.008512850850820541, 0.050408460199832916, 0.006622892338782549, -0.01491487491875887, 0.07007163763046265, 0.035408280... |
40,380 | 40,380 | ['Guy Bresler', 'Elchanan Mossel', 'Allan Sly'] | 0712.1402v2 | Markov random fields are used to model high dimensional distributions in a
number of applied areas. Much recent interest has been devoted to the
reconstruction of the dependency structure from independent samples from the
Markov random fields. We analyze a simple algorithm for reconstructing the
underlying graph defini... | Reconstruction of Markov Random Fields from Samples: Some Easy
Observations and Algorithms | 2,007 | http://arxiv.org/pdf/0712.1402v2 | Title Reconstruction Markov Random Fields Samples Easy Observations Algorithms Summary Markov random field used model high dimensional distribution number applied area Much recent interest devoted reconstruction dependency structure independent sample Markov random field analyze simple algorithm reconstructing underlyi... | [-0.02002720721065998, 0.007050168700516224, 0.03337382525205612, 0.015311664901673794, -0.04680567979812622, -0.03768836334347725, -0.0029729593079537153, 0.037896204739809036, -0.006564808543771505, 0.00229436531662941, 0.046418339014053345, 0.007861526682972908, 0.025372428819537163, 0.009404703043401241, -0.0122527... |
40,381 | 40,381 | ['Fangwen Fu', 'Mihaela van der Schaar'] | 0712.2497v1 | Cross-layer optimization solutions have been proposed in recent years to
improve the performance of network users operating in a time-varying,
error-prone wireless environment. However, these solutions often rely on ad-hoc
optimization approaches, which ignore the different environmental dynamics
experienced at various... | A New Theoretic Foundation for Cross-Layer Optimization | 2,007 | http://arxiv.org/pdf/0712.2497v1 | Title New Theoretic Foundation CrossLayer Optimization Summary Crosslayer optimization solution proposed recent year improve performance network user operating timevarying errorprone wireless environment However solution often rely adhoc optimization approach ignore different environmental dynamic experienced various l... | [-0.027321645990014076, -0.07221289724111557, -0.006538156885653734, -0.03312190622091293, -0.05028734728693962, -0.04054689034819603, 0.005719343665987253, -0.021426349878311157, -0.0398302786052227, -0.04282001033425331, 0.006736149080097675, 0.07468825578689575, 0.023714961484074593, -0.023006407544016838, -0.036705... |
40,382 | 40,382 | ['Jian-Guo Liu', 'Bing-Hong Wang', 'Qiang Guo'] | 0712.3807v3 | In this paper, we propose a spreading activation approach for collaborative
filtering (SA-CF). By using the opinion spreading process, the similarity
between any users can be obtained. The algorithm has remarkably higher accuracy
than the standard collaborative filtering (CF) using Pearson correlation.
Furthermore, we ... | Improved Collaborative Filtering Algorithm via Information
Transformation | 2,007 | http://arxiv.org/pdf/0712.3807v3 | Title Improved Collaborative Filtering Algorithm via Information Transformation Summary paper propose spreading activation approach collaborative filtering SACF using opinion spreading process similarity user obtained algorithm remarkably higher accuracy standard collaborative filtering CF using Pearson correlation Fur... | [0.02866274304687977, -0.007590361870825291, 0.009853030554950237, -0.015642546117305756, -0.024221936240792274, -0.029364116489887238, -0.0163565706461668, 0.028425725176930428, -0.037624016404151917, -0.014337044209241867, -0.09412544965744019, 0.027948331087827682, 0.009008191525936127, 0.03573642671108246, -0.04418... |
40,383 | 40,383 | ['Olivier Cappé', 'Eric Moulines'] | 0712.4273v4 | In this contribution, we propose a generic online (also sometimes called
adaptive or recursive) version of the Expectation-Maximisation (EM) algorithm
applicable to latent variable models of independent observations. Compared to
the algorithm of Titterington (1984), this approach is more directly connected
to the usual... | Online EM Algorithm for Latent Data Models | 2,007 | http://arxiv.org/pdf/0712.4273v4 | Title Online EM Algorithm Latent Data Models Summary contribution propose generic online also sometimes called adaptive recursive version ExpectationMaximisation EM algorithm applicable latent variable model independent observation Compared algorithm Titterington 1984 approach directly connected usual EM algorithm rely... | [0.012554941698908806, 0.03921668976545334, -0.025528615340590477, -0.034347448498010635, -0.01519275177270174, 0.019795158877968788, 0.032702963799238205, -0.01988157629966736, -0.03209753707051277, 0.00796447042375803, 0.07040960341691971, 0.033402860164642334, 0.03859511762857437, 0.042114924639463425, 0.04065413400... |
40,384 | 40,384 | ['Oya Aran', 'Ismail Ari', 'Alexandre Benoit', 'Ana Huerta Carrillo', 'François-Xavier Fanard', 'Pavel Campr', 'Lale Akarun', 'Alice Caplier', 'Michele Rombaut', 'Bulent Sankur'] | 0802.2428v1 | In this project, we have developed a sign language tutor that lets users
learn isolated signs by watching recorded videos and by trying the same signs.
The system records the user's video and analyses it. If the sign is recognized,
both verbal and animated feedback is given to the user. The system is able to
recognize ... | Sign Language Tutoring Tool | 2,008 | http://arxiv.org/pdf/0802.2428v1 | Title Sign Language Tutoring Tool Summary project developed sign language tutor let user learn isolated sign watching recorded video trying sign system record user video analysis sign recognized verbal animated feedback given user system able recognize complex sign involve hand gesture head movement expression performa... | [-0.0016801694873720407, -0.011021817103028297, 0.0017822717782109976, 0.011433376930654049, -0.021405305713415146, 0.02283545956015587, 0.07526860386133194, 0.049056511372327805, 0.04696378856897354, -0.0358690544962883, 0.001993706449866295, 0.0029502580873668194, 0.04403338581323624, 0.050355829298496246, 0.01007497... |
40,385 | 40,385 | ['S. Charles Brubaker', 'Santosh S. Vempala'] | 0804.3575v2 | We present a new algorithm for clustering points in R^n. The key property of
the algorithm is that it is affine-invariant, i.e., it produces the same
partition for any affine transformation of the input. It has strong guarantees
when the input is drawn from a mixture model. For a mixture of two arbitrary
Gaussians, the... | Isotropic PCA and Affine-Invariant Clustering | 2,008 | http://arxiv.org/pdf/0804.3575v2 | Title Isotropic PCA AffineInvariant Clustering Summary present new algorithm clustering point Rn key property algorithm affineinvariant ie produce partition affine transformation input strong guarantee input drawn mixture model mixture two arbitrary Gaussians algorithm correctly classifies sample assuming two component... | [-0.04106396064162254, -0.01223716326057911, -0.0489683635532856, 0.04134663566946983, -0.0025425872299820185, 0.02316054329276085, 0.05475662276148796, 0.050227608531713486, -0.020846117287874222, 0.015991531312465668, -0.0010003872448578477, 0.03324151411652565, 0.048887062817811966, 0.0029854539316147566, 0.01443336... |
40,386 | 40,386 | ['Jian Ma', 'Zengqi Sun'] | 0804.4451v1 | We propose a new framework for dependence structure learning via copula.
Copula is a statistical theory on dependence and measurement of association.
Graphical models are considered as a type of special case of copula families,
named product copula. In this paper, a nonparametric algorithm for copula
estimation is pres... | Dependence Structure Estimation via Copula | 2,008 | http://arxiv.org/pdf/0804.4451v1 | Title Dependence Structure Estimation via Copula Summary propose new framework dependence structure learning via copula Copula statistical theory dependence measurement association Graphical model considered type special case copula family named product copula paper nonparametric algorithm copula estimation presented C... | [-0.03546909615397453, 0.060579393059015274, -0.01690971851348877, -0.014370152726769447, -0.032091762870550156, -0.023498810827732086, 0.03459377586841583, -0.012890081852674484, -0.005006991792470217, -0.024624565616250038, 0.021233638748526573, 0.02535344287753105, 0.03730420768260956, 0.008250618353486061, 0.000215... |
40,387 | 40,387 | ['Takeshi Hirama', 'Koji Hukushima'] | 0805.1480v1 | On-line learning of a hierarchical learning model is studied by a method from
statistical mechanics. In our model a student of a simple perceptron learns
from not a true teacher directly, but ensemble teachers who learn from the true
teacher with a perceptron learning rule. Since the true teacher and the
ensemble teach... | On-line Learning of an Unlearnable True Teacher through Mobile Ensemble
Teachers | 2,008 | http://arxiv.org/pdf/0805.1480v1 | Title Online Learning Unlearnable True Teacher Mobile Ensemble Teachers Summary Online learning hierarchical learning model studied method statistical mechanic model student simple perceptron learns true teacher directly ensemble teacher learn true teacher perceptron learning rule Since true teacher ensemble teacher ex... | [0.001248262356966734, -0.0004902067012153566, -0.031547464430332184, -0.028915414586663246, 0.0026942878030240536, -0.0036542105954140425, 0.036374397575855255, -0.03935813158750534, -0.04382794350385666, -0.03610620275139809, 0.016028709709644318, 0.002357564168050885, -0.0009644554811529815, -0.0006485800840891898, ... |
40,388 | 40,388 | ['Andreas Maurer'] | 0805.2362v1 | We prove existence and uniqueness of the minimizer for the average geodesic
distance to the points of a geodesically convex set on the sphere. This implies
a corresponding existence and uniqueness result for an optimal algorithm for
halfspace learning, when data and target functions are drawn from the uniform
distribut... | An optimization problem on the sphere | 2,008 | http://arxiv.org/pdf/0805.2362v1 | Title optimization problem sphere Summary prove existence uniqueness minimizer average geodesic distance point geodesically convex set sphere implies corresponding existence uniqueness result optimal algorithm halfspace learning data target function drawn uniform distribution Authors 0 Ahmed Osman Wojciech Samek 1 Ji Y... | [-0.01982203684747219, -0.028518570587038994, -0.020159509032964706, 0.03492113947868347, 0.0035457375925034285, -0.008147124201059341, 0.03244812414050102, -0.018990401178598404, -0.03625944256782532, 0.00203523738309741, 0.062098342925310135, -0.006037512794137001, 0.0056206341832876205, 0.025768866762518883, 0.01787... |
40,389 | 40,389 | ['Jayakrishnan Unnikrishnan', 'Venugopal Veeravalli'] | 0807.2677v4 | We study the problem of dynamic spectrum sensing and access in cognitive
radio systems as a partially observed Markov decision process (POMDP). A group
of cognitive users cooperatively tries to exploit vacancies in primary
(licensed) channels whose occupancies follow a Markovian evolution. We first
consider the scenari... | Algorithms for Dynamic Spectrum Access with Learning for Cognitive Radio | 2,008 | http://arxiv.org/pdf/0807.2677v4 | Title Algorithms Dynamic Spectrum Access Learning Cognitive Radio Summary study problem dynamic spectrum sensing access cognitive radio system partially observed Markov decision process POMDP group cognitive user cooperatively try exploit vacancy primary licensed channel whose occupancy follow Markovian evolution first... | [0.014059891924262047, 0.0027055274695158005, -0.01015104353427887, -0.08248133212327957, -0.03865718096494675, -0.020564952865242958, -0.05573679506778717, -0.01600140891969204, -0.04022417590022087, 0.0006165951490402222, 0.007024472113698721, 0.046535100787878036, 0.0021578192245215178, 0.012544848024845123, -0.0438... |
40,390 | 40,390 | ['Sébastien Gambs'] | 0809.0444v2 | Quantum classification is defined as the task of predicting the associated
class of an unknown quantum state drawn from an ensemble of pure states given a
finite number of copies of this state. By recasting the state discrimination
problem within the framework of Machine Learning (ML), we can use the notion of
learning... | Quantum classification | 2,008 | http://arxiv.org/pdf/0809.0444v2 | Title Quantum classification Summary Quantum classification defined task predicting associated class unknown quantum state drawn ensemble pure state given finite number copy state recasting state discrimination problem within framework Machine Learning ML use notion learning reduction coming classical ML solve differen... | [-0.031184272840619087, 0.04983370378613472, -0.030837761238217354, 0.033309683203697205, -0.031116167083382607, -0.010906513780355453, -0.032786138355731964, 0.060010477900505066, 0.014084713533520699, -0.0484127402305603, 0.03162878751754761, -0.006538889370858669, -0.009811927564442158, 0.03851470351219177, 0.013840... |
40,391 | 40,391 | ['Robert Kleinberg', 'Aleksandrs Slivkins', 'Eli Upfal'] | 0809.4882v1 | In a multi-armed bandit problem, an online algorithm chooses from a set of
strategies in a sequence of trials so as to maximize the total payoff of the
chosen strategies. While the performance of bandit algorithms with a small
finite strategy set is quite well understood, bandit problems with large
strategy sets are st... | Multi-Armed Bandits in Metric Spaces | 2,008 | http://arxiv.org/pdf/0809.4882v1 | Title MultiArmed Bandits Metric Spaces Summary multiarmed bandit problem online algorithm chooses set strategy sequence trial maximize total payoff chosen strategy performance bandit algorithm small finite strategy set quite well understood bandit problem large strategy set still topic active investigation motivated pr... | [-0.01805427297949791, 0.048686038702726364, -0.025416262447834015, -0.024830034002661705, -0.01969464309513569, -0.002948541659861803, 0.03532818332314491, 0.05070574954152107, 0.023200388997793198, -0.00914902426302433, -0.02249598503112793, -0.015616154298186302, -0.04976318031549454, 0.03517523407936096, 0.04651300... |
40,392 | 40,392 | ['Ping Li'] | 0811.1250v1 | We develop the concept of ABC-Boost (Adaptive Base Class Boost) for
multi-class classification and present ABC-MART, a concrete implementation of
ABC-Boost. The original MART (Multiple Additive Regression Trees) algorithm has
been very successful in large-scale applications. For binary classification,
ABC-MART recovers... | Adaptive Base Class Boost for Multi-class Classification | 2,008 | http://arxiv.org/pdf/0811.1250v1 | Title Adaptive Base Class Boost Multiclass Classification Summary develop concept ABCBoost Adaptive Base Class Boost multiclass classification present ABCMART concrete implementation ABCBoost original MART Multiple Additive Regression Trees algorithm successful largescale application binary classification ABCMART recov... | [-0.03553744778037071, 0.05258772894740105, -0.027778713032603264, 0.0035817197058349848, 0.025501905009150505, 0.012923954986035824, 0.012519453652203083, 0.03570367768406868, -0.05567505583167076, -0.05523454025387764, 0.016336312517523766, 0.014719998463988304, 0.0038095396012067795, 0.02514777146279812, -0.01155230... |
40,393 | 40,393 | ['Hendrik Blockeel', 'Robert Brijder'] | 0901.4876v1 | Grammar inference deals with determining (preferable simple) models/grammars
consistent with a set of observations. There is a large body of research on
grammar inference within the theory of formal languages. However, there is
surprisingly little known on grammar inference for graph grammars. In this
paper we take a f... | Non-Confluent NLC Graph Grammar Inference by Compressing Disjoint
Subgraphs | 2,009 | http://arxiv.org/pdf/0901.4876v1 | Title NonConfluent NLC Graph Grammar Inference Compressing Disjoint Subgraphs Summary Grammar inference deal determining preferable simple modelsgrammars consistent set observation large body research grammar inference within theory formal language However surprisingly little known grammar inference graph grammar paper... | [0.021713918074965477, 0.0537232831120491, -0.027525344863533974, 0.05019339546561241, -0.0670439675450325, 0.0025261922273784876, -0.02442631684243679, 0.050123829394578934, 0.03851746395230293, -0.008947000838816166, 0.024649841710925102, 0.0038888296112418175, -0.007258756551891565, 0.007502388674765825, 0.027671592... |
40,394 | 40,394 | ['Nima Mirbakhsh', 'Arman Didandeh'] | 0902.2751v4 | Classification of some objects in classes of concepts is an essential and
even breathtaking task in many applications. A solution is discussed here based
on Multi-Agent systems. A kernel of some expert agents in several classes is to
consult a central agent decide among the classification problem of a certain
object. T... | Object Classification by means of Multi-Feature Concept Learning in a
Multi Expert-Agent System | 2,009 | http://arxiv.org/pdf/0902.2751v4 | Title Object Classification mean MultiFeature Concept Learning Multi ExpertAgent System Summary Classification object class concept essential even breathtaking task many application solution discussed based MultiAgent system kernel expert agent several class consult central agent decide among classification problem cer... | [0.0344855971634388, 0.011442185379564762, -0.020186977460980415, -0.0005703498027287424, -0.022094884887337685, -0.007417473942041397, 0.09136312454938889, 0.006954249460250139, -0.028922071680426598, -0.06617054343223572, 0.010255109518766403, 0.04188120365142822, -0.024818694218993187, 0.05053127929568291, -0.028488... |
40,395 | 40,395 | ['Nisheeth Srivastava'] | 0904.0648v1 | We show that Boolean functions expressible as monotone disjunctive normal
forms are PAC-evolvable under a uniform distribution on the Boolean cube if the
hypothesis size is allowed to remain fixed. We further show that this result is
insufficient to prove the PAC-learnability of monotone Boolean functions,
thereby demo... | Evolvability need not imply learnability | 2,009 | http://arxiv.org/pdf/0904.0648v1 | Title Evolvability need imply learnability Summary show Boolean function expressible monotone disjunctive normal form PACevolvable uniform distribution Boolean cube hypothesis size allowed remain fixed show result insufficient prove PAClearnability monotone Boolean function thereby demonstrating counterexample recent c... | [-0.03058527782559395, 0.03131340444087982, -0.02800724469125271, -0.02221195586025715, -0.01884452998638153, 0.00124327652156353, 0.011184152215719223, -0.008212610147893429, 0.01817239262163639, 0.024372542276978493, 0.0485285185277462, 0.07442198693752289, -0.03318434953689575, 0.09816990792751312, -0.00167848949786... |
40,396 | 40,396 | ['Navin Goyal', 'Luis Rademacher'] | 0904.1227v1 | We show that learning a convex body in $\RR^d$, given random samples from the
body, requires $2^{\Omega(\sqrt{d/\eps})}$ samples. By learning a convex body
we mean finding a set having at most $\eps$ relative symmetric difference with
the input body. To prove the lower bound we construct a hard to learn family of
conve... | Learning convex bodies is hard | 2,009 | http://arxiv.org/pdf/0904.1227v1 | Title Learning convex body hard Summary show learning convex body RRd given random sample body requires 2Omegasqrtdeps sample learning convex body mean finding set eps relative symmetric difference input body prove lower bound construct hard learn family convex body construction family simple based error correcting cod... | [-0.020417779684066772, -0.02734203264117241, -0.029933370649814606, 0.030833197757601738, 0.004273048136383295, 0.0011294054565951228, 0.012416304089128971, 0.017062939703464508, -0.07624825835227966, 0.009277394972741604, 0.05101991817355156, -0.00015692418674007058, 0.022897958755493164, 0.006748958956450224, 0.0135... |
40,397 | 40,397 | ['Sherief Abdallah'] | 0904.2320v1 | Experimental verification has been the method of choice for verifying the
stability of a multi-agent reinforcement learning (MARL) algorithm as the
number of agents grows and theoretical analysis becomes prohibitively complex.
For cooperative agents, where the ultimate goal is to optimize some global
metric, the stabil... | Why Global Performance is a Poor Metric for Verifying Convergence of
Multi-agent Learning | 2,009 | http://arxiv.org/pdf/0904.2320v1 | Title Global Performance Poor Metric Verifying Convergence Multiagent Learning Summary Experimental verification method choice verifying stability multiagent reinforcement learning MARL algorithm number agent grows theoretical analysis becomes prohibitively complex cooperative agent ultimate goal optimize global metric... | [-0.016869602724909782, 0.021560490131378174, -0.014069616794586182, -0.027232740074396133, -0.02690959721803665, -0.025734545662999153, 0.006047270726412535, -0.008936585858464241, -0.034257300198078156, 0.018778061494231224, 0.007693853694945574, 0.0028343431185930967, -0.00707523338496685, 0.040984950959682465, 0.00... |
40,398 | 40,398 | ['Takeaki Uno', 'Masashi Sugiyama', 'Koji Tsuda'] | 0904.3151v1 | Neighborhood graphs are gaining popularity as a concise data representation
in machine learning. However, naive graph construction by pairwise distance
calculation takes $O(n^2)$ runtime for $n$ data points and this is
prohibitively slow for millions of data points. For strings of equal length,
the multiple sorting met... | Efficient Construction of Neighborhood Graphs by the Multiple Sorting
Method | 2,009 | http://arxiv.org/pdf/0904.3151v1 | Title Efficient Construction Neighborhood Graphs Multiple Sorting Method Summary Neighborhood graph gaining popularity concise data representation machine learning However naive graph construction pairwise distance calculation take On2 runtime n data point prohibitively slow million data point string equal length multi... | [-0.03725392743945122, 0.020433098077774048, -0.013058427721261978, 0.007166039664298296, -0.03402794897556305, -0.05556119978427887, 0.061940230429172516, 0.01944047585129738, 0.037818532437086105, 0.0010915333405137062, 0.015070340596139431, 0.05815873667597771, 0.014535663649439812, 0.022031648084521294, -0.00699290... |
40,399 | 40,399 | ['Mattheos K. Protopapas', 'Elias B. Kosmatopoulos', 'Francesco Battaglia'] | 0905.3640v1 | We use co-evolutionary genetic algorithms to model the players' learning
process in several Cournot models, and evaluate them in terms of their
convergence to the Nash Equilibrium. The "social-learning" versions of the two
co-evolutionary algorithms we introduce, establish Nash Equilibrium in those
models, in contrast ... | Coevolutionary Genetic Algorithms for Establishing Nash Equilibrium in
Symmetric Cournot Games | 2,009 | http://arxiv.org/pdf/0905.3640v1 | Title Coevolutionary Genetic Algorithms Establishing Nash Equilibrium Symmetric Cournot Games Summary use coevolutionary genetic algorithm model player learning process several Cournot model evaluate term convergence Nash Equilibrium sociallearning version two coevolutionary algorithm introduce establish Nash Equilibri... | [0.019385816529393196, -0.006554223597049713, -0.032135579735040665, -0.009397466666996479, -0.06866031140089035, -0.04077601805329323, -0.015168067067861557, -0.01883877068758011, 0.007680327165871859, -0.0006538053858093917, 0.0297732912003994, 0.023372860625386238, -0.005795432720333338, 0.0472281239926815, 0.018491... |
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