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40,310 | TOMAAT: volumetric medical image analysis as a cloud service | cs.CV | 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... | computer science |
40,311 | Adaptive Polar Active Contour for Segmentation and Tracking in
Ultrasound Videos | eess.IV | 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... | computer science |
40,312 | Fusion of stereo and still monocular depth estimates in a
self-supervised learning context | cs.CV | 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. ... | computer science |
40,313 | A Survey of Deep Learning Techniques for Mobile Robot Applications | cs.CV | 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. | computer science |
40,314 | Joint 3D Face Reconstruction and Dense Alignment with Position Map
Regression Network | cs.CV | 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 ... | computer science |
40,315 | Densely Connected Pyramid Dehazing Network | cs.CV | 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... | computer science |
40,316 | How accurate are the time delay estimates in gravitational lensing? | cs.LG | 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... | computer science |
40,317 | Practical algorithms for on-line sampling | cs.LG | 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... | computer science |
40,318 | Predicting the expected behavior of agents that learn about agents: the
CLRI framework | cs.MA | 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... | computer science |
40,319 | MOO: A Methodology for Online Optimization through Mining the Offline
Optimum | cs.DS | 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... | computer science |
40,320 | Data Mining to Measure and Improve the Success of Web Sites | cs.LG | 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... | computer science |
40,321 | Design of an Electro-Hydraulic System Using Neuro-Fuzzy Techniques | cs.RO | 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... | computer science |
40,322 | Torque Ripple Minimization in a Switched Reluctance Drive by Neuro-Fuzzy
Compensation | cs.RO | 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... | computer science |
40,323 | A Fuzzy Relational Identification Algorithm and Its Application to
Predict The Behaviour of a Motor Drive System | cs.RO | 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... | computer science |
40,324 | Applications of Data Mining to Electronic Commerce | cs.LG | 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... | computer science |
40,325 | Fault Detection using Immune-Based Systems and Formal Language
Algorithms | cs.CE | 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... | computer science |
40,326 | Web Mining Research: A Survey | cs.LG | 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... | computer science |
40,327 | Provably Fast and Accurate Recovery of Evolutionary Trees through
Harmonic Greedy Triplets | cs.DS | 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... | computer science |
40,328 | Learning to Cooperate via Policy Search | cs.LG | 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... | computer science |
40,329 | Bipartite graph partitioning and data clustering | cs.IR | 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... | computer science |
40,330 | Machine Learning in Automated Text Categorization | cs.IR | 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... | computer science |
40,331 | The performance of the batch learner algorithm | cs.LG | 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 \... | computer science |
40,332 | The Dynamics of AdaBoost Weights Tells You What's Hard to Classify | cs.LG | 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 ... | computer science |
40,333 | Learning to Play Games in Extensive Form by Valuation | cs.LG | 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... | computer science |
40,334 | On Learning by Exchanging Advice | cs.LG | 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... | computer science |
40,335 | Capturing Knowledge of User Preferences: ontologies on recommender
systems | cs.LG | 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... | computer science |
40,336 | Interface agents: A review of the field | cs.MA | 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 ... | computer science |
40,337 | Exploiting Synergy Between Ontologies and Recommender Systems | cs.LG | 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... | computer science |
40,338 | Required sample size for learning sparse Bayesian networks with many
variables | cs.LG | 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... | computer science |
40,339 | Mining the Web for Lexical Knowledge to Improve Keyphrase Extraction:
Learning from Labeled and Unlabeled Data | cs.LG | 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... | computer science |
40,340 | Unsupervised Learning of Semantic Orientation from a
Hundred-Billion-Word Corpus | cs.LG | 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... | computer science |
40,341 | Learning to Extract Keyphrases from Text | cs.LG | 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... | computer science |
40,342 | Extraction of Keyphrases from Text: Evaluation of Four Algorithms | cs.LG | 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 ... | computer science |
40,343 | Mapping Subsets of Scholarly Information | cs.IR | 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. | computer science |
40,344 | Semantic Linking - a Context-Based Approach to Interactivity in
Hypermedia | cs.IR | 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... | computer science |
40,345 | Hypermedia Learning Objects System - On the Way to a Semantic
Educational Web | cs.IR | 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... | computer science |
40,346 | Online convex optimization in the bandit setting: gradient descent
without a gradient | cs.LG | 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... | computer science |
40,347 | Journal of New Democratic Methods: An Introduction | cs.CY | 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... | computer science |
40,348 | On sample complexity for computational pattern recognition | cs.LG | 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... | computer science |
40,349 | Selection in Scale-Free Small World | cs.LG | 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... | computer science |
40,350 | The Signed Distance Function: A New Tool for Binary Classification | cs.LG | 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 ... | computer science |
40,351 | Parameter Estimation of Hidden Diffusion Processes: Particle Filter vs.
Modified Baum-Welch Algorithm | cs.DS | 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... | computer science |
40,352 | Online Learning and Resource-Bounded Dimension: Winnow Yields New Lower
Bounds for Hard Sets | cs.CC | 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... | computer science |
40,353 | How to Beat the Adaptive Multi-Armed Bandit | cs.DS | 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... | computer science |
40,354 | Metric State Space Reinforcement Learning for a Vision-Capable Mobile
Robot | cs.RO | 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... | computer science |
40,355 | Revealing the Autonomous System Taxonomy: The Machine Learning Approach | cs.NI | 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 ... | computer science |
40,356 | HCI and Educational Metrics as Tools for VLE Evaluation | cs.HC | 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... | computer science |
40,357 | Query Chains: Learning to Rank from Implicit Feedback | cs.LG | 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... | computer science |
40,358 | Evaluating the Robustness of Learning from Implicit Feedback | cs.LG | 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... | computer science |
40,359 | Minimally Invasive Randomization for Collecting Unbiased Preferences
from Clickthrough Logs | cs.IR | 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... | computer science |
40,360 | The generating function of the polytope of transport matrices $U(r,c)$
as a positive semidefinite kernel of the marginals $r$ and $c$ | cs.LG | This paper has been withdrawn by the author due to a crucial error in the
proof of Lemma 5. | computer science |
40,361 | Motion Primitives for Robotic Flight Control | cs.RO | 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... | computer science |
40,362 | Mining Generalized Graph Patterns based on User Examples | cs.DS | 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... | computer science |
40,363 | A Relational Approach to Functional Decomposition of Logic Circuits | cs.DM | 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... | computer science |
40,364 | CSCR:Computer Supported Collaborative Research | cs.HC | 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. | computer science |
40,365 | A Delta Debugger for ILP Query Execution | cs.PL | 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 ... | computer science |
40,366 | Learning Complexity Dimensions for a Continuous-Time Control System | math.OC | 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 ... | computer science |
40,367 | A Model for Prejudiced Learning in Noisy Environments | nlin.AO | 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 ... | computer science |
40,368 | Combinatorial Approach to Object Analysis | nlin.AO | 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 | computer science |
40,369 | Metric learning pairwise kernel for graph inference | cs.LG | 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... | computer science |
40,370 | Improved Bounds on Quantum Learning Algorithms | cs.LG | 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 ... | computer science |
40,371 | Statistical Mechanics of Nonlinear On-line Learning for Ensemble
Teachers | cs.LG | 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... | computer science |
40,372 | Quantum Algorithms for Learning and Testing Juntas | cs.LG | 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... | computer science |
40,373 | Virtual screening with support vector machines and structure kernels | cs.LG | 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... | computer science |
40,374 | A Dichotomy Theorem for General Minimum Cost Homomorphism Problem | cs.LG | 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... | computer science |
40,375 | Filtering Additive Measurement Noise with Maximum Entropy in the Mean | cs.LG | 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... | computer science |
40,376 | Learning for Dynamic Bidding in Cognitive Radio Resources | cs.LG | 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... | computer science |
40,377 | Fast Selection of Spectral Variables with B-Spline Compression | cs.LG | 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... | computer science |
40,378 | Resampling methods for parameter-free and robust feature selection with
mutual information | cs.LG | 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... | computer science |
40,379 | A Universal Kernel for Learning Regular Languages | cs.LG | 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. | computer science |
40,380 | Reconstruction of Markov Random Fields from Samples: Some Easy
Observations and Algorithms | cs.CC | 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... | computer science |
40,381 | A New Theoretic Foundation for Cross-Layer Optimization | cs.NI | 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... | computer science |
40,382 | Improved Collaborative Filtering Algorithm via Information
Transformation | cs.LG | 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 ... | computer science |
40,383 | Online EM Algorithm for Latent Data Models | stat.CO | 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... | computer science |
40,384 | Sign Language Tutoring Tool | cs.LG | 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 ... | computer science |
40,385 | Isotropic PCA and Affine-Invariant Clustering | cs.LG | 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... | computer science |
40,386 | Dependence Structure Estimation via Copula | cs.LG | 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... | computer science |
40,387 | On-line Learning of an Unlearnable True Teacher through Mobile Ensemble
Teachers | cs.LG | 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... | computer science |
40,388 | An optimization problem on the sphere | cs.LG | 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... | computer science |
40,389 | Algorithms for Dynamic Spectrum Access with Learning for Cognitive Radio | cs.NI | 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... | computer science |
40,390 | Quantum classification | cs.LG | 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... | computer science |
40,391 | Multi-Armed Bandits in Metric Spaces | cs.DS | 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... | computer science |
40,392 | Adaptive Base Class Boost for Multi-class Classification | cs.LG | 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... | computer science |
40,393 | Non-Confluent NLC Graph Grammar Inference by Compressing Disjoint
Subgraphs | cs.LG | 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... | computer science |
40,394 | Object Classification by means of Multi-Feature Concept Learning in a
Multi Expert-Agent System | cs.MA | 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... | computer science |
40,395 | Evolvability need not imply learnability | cs.LG | 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... | computer science |
40,396 | Learning convex bodies is hard | cs.LG | 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... | computer science |
40,397 | Why Global Performance is a Poor Metric for Verifying Convergence of
Multi-agent Learning | cs.MA | 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... | computer science |
40,398 | Efficient Construction of Neighborhood Graphs by the Multiple Sorting
Method | cs.DS | 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... | computer science |
40,399 | Coevolutionary Genetic Algorithms for Establishing Nash Equilibrium in
Symmetric Cournot Games | cs.GT | 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 ... | computer science |
40,400 | Online Learning of Assignments that Maximize Submodular Functions | cs.LG | Which ads should we display in sponsored search in order to maximize our
revenue? How should we dynamically rank information sources to maximize value
of information? These applications exhibit strong diminishing returns:
Selection of redundant ads and information sources decreases their marginal
utility. We show that ... | computer science |
40,401 | An Application of Bayesian classification to Interval Encoded Temporal
mining with prioritized items | cs.DB | In real life, media information has time attributes either implicitly or
explicitly known as temporal data. This paper investigates the usefulness of
applying Bayesian classification to an interval encoded temporal database with
prioritized items. The proposed method performs temporal mining by encoding the
database wi... | computer science |
40,402 | Sharp Dichotomies for Regret Minimization in Metric Spaces | cs.DS | The Lipschitz multi-armed bandit (MAB) problem generalizes the classical
multi-armed bandit problem by assuming one is given side information consisting
of a priori upper bounds on the difference in expected payoff between certain
pairs of strategies. Classical results of (Lai and Robbins 1985) and (Auer et
al. 2002) i... | computer science |
40,403 | A Dynamic Near-Optimal Algorithm for Online Linear Programming | cs.DS | A natural optimization model that formulates many online resource allocation
and revenue management problems is the online linear program (LP) in which the
constraint matrix is revealed column by column along with the corresponding
objective coefficient. In such a model, a decision variable has to be set each
time a co... | computer science |
40,404 | Towards Industrialized Conception and Production of Serious Games | cs.LG | Serious Games (SGs) have experienced a tremendous outburst these last years.
Video game companies have been producing fun, user-friendly SGs, but their
educational value has yet to be proven. Meanwhile, cognition research scientist
have been developing SGs in such a way as to guarantee an educational gain, but
the fun ... | computer science |
40,405 | Training a Large Scale Classifier with the Quantum Adiabatic Algorithm | cs.LG | In a previous publication we proposed discrete global optimization as a
method to train a strong binary classifier constructed as a thresholded sum
over weak classifiers. Our motivation was to cast the training of a classifier
into a format amenable to solution by the quantum adiabatic algorithm. Applying
adiabatic qua... | computer science |
40,406 | An ensemble approach for feature selection of Cyber Attack Dataset | cs.CR | Feature selection is an indispensable preprocessing step when mining huge
datasets that can significantly improve the overall system performance.
Therefore in this paper we focus on a hybrid approach of feature selection.
This method falls into two phases. The filter phase select the features with
highest information g... | computer science |
40,407 | The Gaussian Surface Area and Noise Sensitivity of Degree-$d$
Polynomials | cs.CC | We provide asymptotically sharp bounds for the Gaussian surface area and the
Gaussian noise sensitivity of polynomial threshold functions. In particular we
show that if $f$ is a degree-$d$ polynomial threshold function, then its
Gaussian sensitivity at noise rate $\epsilon$ is less than some quantity
asymptotic to $\fr... | computer science |
40,408 | Application of k Means Clustering algorithm for prediction of Students
Academic Performance | cs.LG | The ability to monitor the progress of students academic performance is a
critical issue to the academic community of higher learning. A system for
analyzing students results based on cluster analysis and uses standard
statistical algorithms to arrange their scores data according to the level of
their performance is de... | computer science |
40,409 | A Complete Characterization of Statistical Query Learning with
Applications to Evolvability | cs.CC | Statistical query (SQ) learning model of Kearns (1993) is a natural
restriction of the PAC learning model in which a learning algorithm is allowed
to obtain estimates of statistical properties of the examples but cannot see
the examples themselves. We describe a new and simple characterization of the
query complexity o... | computer science |
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