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40,911 | An Architecture of Active Learning SVMs with Relevance Feedback for
Classifying E-mail | cs.IR | In this paper, we have proposed an architecture of active learning SVMs with
relevance feedback (RF)for classifying e-mail. This architecture combines both
active learning strategies where instead of using a randomly selected training
set, the learner has access to a pool of unlabeled instances and can request
the labe... | computer science |
40,912 | Indexability, concentration, and VC theory | cs.DS | Degrading performance of indexing schemes for exact similarity search in high
dimensions has long since been linked to histograms of distributions of
distances and other 1-Lipschitz functions getting concentrated. We discuss this
observation in the framework of the phenomenon of concentration of measure on
the structur... | computer science |
40,913 | A Smoothing Stochastic Gradient Method for Composite Optimization | math.OC | We consider the unconstrained optimization problem whose objective function
is composed of a smooth and a non-smooth conponents where the smooth component
is the expectation a random function. This type of problem arises in some
interesting applications in machine learning. We propose a stochastic gradient
descent algo... | computer science |
40,914 | Clustering under Perturbation Resilience | cs.LG | Motivated by the fact that distances between data points in many real-world
clustering instances are often based on heuristic measures, Bilu and
Linial~\cite{BL} proposed analyzing objective based clustering problems under
the assumption that the optimum clustering to the objective is preserved under
small multiplicati... | computer science |
40,915 | Multi-timescale Nexting in a Reinforcement Learning Robot | cs.LG | The term "nexting" has been used by psychologists to refer to the propensity
of people and many other animals to continually predict what will happen next
in an immediate, local, and personal sense. The ability to "next" constitutes a
basic kind of awareness and knowledge of one's environment. In this paper we
present ... | computer science |
40,916 | SLA Establishment with Guaranteed QoS in the Interdomain Network: A
Stock Model | cs.NI | The new model that we present in this paper is introduced in the context of
guaranteed QoS and resources management in the inter-domain routing framework.
This model, called the stock model, is based on a reverse cascade approach and
is applied in a distributed context. So transit providers have to learn the
right capa... | computer science |
40,917 | Using Taxonomies to Facilitate the Analysis of the Association Rules | cs.DB | The Data Mining process enables the end users to analyze, understand and use
the extracted knowledge in an intelligent system or to support in the
decision-making processes. However, many algorithms used in the process
encounter large quantities of patterns, complicating the analysis of the
patterns. This fact occurs w... | computer science |
40,918 | Chinese Restaurant Game - Part II: Applications to Wireless Networking,
Cloud Computing, and Online Social Networking | cs.SI | In Part I of this two-part paper [1], we proposed a new game, called Chinese
restaurant game, to analyze the social learning problem with negative network
externality. The best responses of agents in the Chinese restaurant game with
imperfect signals are constructed through a recursive method, and the influence
of both... | computer science |
40,919 | Chinese Restaurant Game - Part I: Theory of Learning with Negative
Network Externality | cs.SI | In a social network, agents are intelligent and have the capability to make
decisions to maximize their utilities. They can either make wise decisions by
taking advantages of other agents' experiences through learning, or make
decisions earlier to avoid competitions from huge crowds. Both these two
effects, social lear... | computer science |
40,920 | Low-rank optimization with trace norm penalty | math.OC | The paper addresses the problem of low-rank trace norm minimization. We
propose an algorithm that alternates between fixed-rank optimization and
rank-one updates. The fixed-rank optimization is characterized by an efficient
factorization that makes the trace norm differentiable in the search space and
the computation o... | computer science |
40,921 | A new order theory of set systems and better quasi-orderings | math.CO | By reformulating a learning process of a set system L as a game between
Teacher (presenter of data) and Learner (updater of the abstract independent
set), we define the order type dim L of L to be the order type of the game
tree. The theory of this new order type and continuous, monotone function
between set systems co... | computer science |
40,922 | Online Learning for Classification of Low-rank Representation Features
and Its Applications in Audio Segment Classification | cs.LG | In this paper, a novel framework based on trace norm minimization for audio
segment is proposed. In this framework, both the feature extraction and
classification are obtained by solving corresponding convex optimization
problem with trace norm regularization. For feature extraction, robust
principle component analysis... | computer science |
40,923 | A Scalable Multiclass Algorithm for Node Classification | cs.LG | We introduce a scalable algorithm, MUCCA, for multiclass node classification
in weighted graphs. Unlike previously proposed methods for the same task, MUCCA
works in time linear in the number of nodes. Our approach is based on a
game-theoretic formulation of the problem in which the test labels are
expressed as a Nash ... | computer science |
40,924 | Ordinal Rating of Network Performance and Inference by Matrix Completion | cs.NI | This paper addresses the large-scale acquisition of end-to-end network
performance. We made two distinct contributions: ordinal rating of network
performance and inference by matrix completion. The former reduces measurement
costs and unifies various metrics which eases their processing in applications.
The latter enab... | computer science |
40,925 | The complexity of learning halfspaces using generalized linear methods | cs.LG | Many popular learning algorithms (E.g. Regression, Fourier-Transform based
algorithms, Kernel SVM and Kernel ridge regression) operate by reducing the
problem to a convex optimization problem over a vector space of functions.
These methods offer the currently best approach to several central problems
such as learning h... | computer science |
40,926 | Explosion prediction of oil gas using SVM and Logistic Regression | cs.CE | The prevention of dangerous chemical accidents is a primary problem of
industrial manufacturing. In the accidents of dangerous chemicals, the oil gas
explosion plays an important role. The essential task of the explosion
prevention is to estimate the better explosion limit of a given oil gas. In
this paper, Support Vec... | computer science |
40,927 | On Calibrated Predictions for Auction Selection Mechanisms | cs.GT | Calibration is a basic property for prediction systems, and algorithms for
achieving it are well-studied in both statistics and machine learning. In many
applications, however, the predictions are used to make decisions that select
which observations are made. This makes calibration difficult, as adjusting
predictions ... | computer science |
40,929 | Online Stochastic Optimization with Multiple Objectives | cs.LG | In this paper we propose a general framework to characterize and solve the
stochastic optimization problems with multiple objectives underlying many real
world learning applications. We first propose a projection based algorithm
which attains an $O(T^{-1/3})$ convergence rate. Then, by leveraging on the
theory of Lagra... | computer science |
40,930 | Quantum support vector machine for big data classification | cs.LG | Supervised machine learning is the classification of new data based on
already classified training examples. In this work, we show that the support
vector machine, an optimized binary classifier, can be implemented on a quantum
computer, with complexity logarithmic in the size of the vectors and the number
of training ... | computer science |
40,931 | Investigating the Detection of Adverse Drug Events in a UK General
Practice Electronic Health-Care Database | cs.CE | Data-mining techniques have frequently been developed for Spontaneous
reporting databases. These techniques aim to find adverse drug events
accurately and efficiently. Spontaneous reporting databases are prone to
missing information, under reporting and incorrect entries. This often results
in a detection lag or preven... | computer science |
40,932 | Application of a clustering framework to UK domestic electricity data | cs.CE | This paper takes an approach to clustering domestic electricity load profiles
that has been successfully used with data from Portugal and applies it to UK
data. Clustering techniques are applied and it is found that the preferred
technique in the Portuguese work (a two stage process combining Self Organised
Maps and Km... | computer science |
40,933 | Creating Personalised Energy Plans. From Groups to Individuals using
Fuzzy C Means Clustering | cs.CE | Changes in the UK electricity market mean that domestic users will be
required to modify their usage behaviour in order that supplies can be
maintained. Clustering allows usage profiles collected at the household level
to be clustered into groups and assigned a stereotypical profile which can be
used to target marketin... | computer science |
40,934 | Examining the Classification Accuracy of TSVMs with ?Feature Selection
in Comparison with the GLAD Algorithm | cs.LG | Gene expression data sets are used to classify and predict patient diagnostic
categories. As we know, it is extremely difficult and expensive to obtain gene
expression labelled examples. Moreover, conventional supervised approaches
cannot function properly when labelled data (training examples) are
insufficient using S... | computer science |
40,935 | Quiet in Class: Classification, Noise and the Dendritic Cell Algorithm | cs.LG | Theoretical analyses of the Dendritic Cell Algorithm (DCA) have yielded
several criticisms about its underlying structure and operation. As a result,
several alterations and fixes have been suggested in the literature to correct
for these findings. A contribution of this work is to investigate the effects
of replacing ... | computer science |
40,936 | Detect adverse drug reactions for drug Alendronate | cs.CE | Adverse drug reaction (ADR) is widely concerned for public health issue. In
this study we propose an original approach to detect the ADRs using feature
matrix and feature selection. The experiments are carried out on the drug
Simvastatin. Major side effects for the drug are detected and better
performance is achieved c... | computer science |
40,937 | Biomarker Clustering of Colorectal Cancer Data to Complement Clinical
Classification | cs.LG | In this paper, we describe a dataset relating to cellular and physical
conditions of patients who are operated upon to remove colorectal tumours. This
data provides a unique insight into immunological status at the point of tumour
removal, tumour classification and post-operative survival. Attempts are made
to cluster ... | computer science |
40,938 | Approximate dynamic programming using fluid and diffusion approximations
with applications to power management | cs.LG | Neuro-dynamic programming is a class of powerful techniques for approximating
the solution to dynamic programming equations. In their most computationally
attractive formulations, these techniques provide the approximate solution only
within a prescribed finite-dimensional function class. Thus, the question that
always... | computer science |
40,939 | Using Clustering to extract Personality Information from socio economic
data | cs.LG | It has become apparent that models that have been applied widely in
economics, including Machine Learning techniques and Data Mining methods,
should take into consideration principles that derive from the theories of
Personality Psychology in order to discover more comprehensive knowledge
regarding complicated economic... | computer science |
40,940 | Finding the creatures of habit; Clustering households based on their
flexibility in using electricity | cs.LG | Changes in the UK electricity market, particularly with the roll out of smart
meters, will provide greatly increased opportunities for initiatives intended
to change households' electricity usage patterns for the benefit of the overall
system. Users show differences in their regular behaviours and clustering
households... | computer science |
40,941 | Unsupervised Gene Expression Data using Enhanced Clustering Method | cs.CE | Microarrays are made it possible to simultaneously monitor the expression
profiles of thousands of genes under various experimental conditions.
Identification of co-expressed genes and coherent patterns is the central goal
in microarray or gene expression data analysis and is an important task in
bioinformatics researc... | computer science |
40,942 | Performance Analysis of Clustering Algorithms for Gene Expression Data | cs.CE | Microarray technology is a process that allows thousands of genes
simultaneously monitor to various experimental conditions. It is used to
identify the co-expressed genes in specific cells or tissues that are actively
used to make proteins, This method is used to analysis the gene expression, an
important task in bioin... | computer science |
40,943 | A Data Management Approach for Dataset Selection Using Human Computation | cs.LG | As the number of applications that use machine learning algorithms increases,
the need for labeled data useful for training such algorithms intensifies.
Getting labels typically involves employing humans to do the annotation,
which directly translates to training and working costs. Crowdsourcing
platforms have made l... | computer science |
40,944 | On Analyzing Estimation Errors due to Constrained Connections in Online
Review Systems | cs.SI | Constrained connection is the phenomenon that a reviewer can only review a
subset of products/services due to narrow range of interests or limited
attention capacity. In this work, we study how constrained connections can
affect estimation performance in online review systems (ORS). We find that
reviewers' constrained ... | computer science |
40,945 | A Comprehensive Evaluation of Machine Learning Techniques for Cancer
Class Prediction Based on Microarray Data | cs.LG | Prostate cancer is among the most common cancer in males and its
heterogeneity is well known. Its early detection helps making therapeutic
decision. There is no standard technique or procedure yet which is full-proof
in predicting cancer class. The genomic level changes can be detected in gene
expression data and those... | computer science |
40,946 | MixedGrad: An O(1/T) Convergence Rate Algorithm for Stochastic Smooth
Optimization | cs.LG | It is well known that the optimal convergence rate for stochastic
optimization of smooth functions is $O(1/\sqrt{T})$, which is same as
stochastic optimization of Lipschitz continuous convex functions. This is in
contrast to optimizing smooth functions using full gradients, which yields a
convergence rate of $O(1/T^2)$... | computer science |
40,947 | A Review of Machine Learning based Anomaly Detection Techniques | cs.LG | Intrusion detection is so much popular since the last two decades where
intrusion is attempted to break into or misuse the system. It is mainly of two
types based on the intrusions, first is Misuse or signature based detection and
the other is Anomaly detection. In this paper Machine learning based methods
which are on... | computer science |
40,948 | Participation anticipating in elections using data mining methods | cs.CY | Anticipating the political behavior of people will be considerable help for
election candidates to assess the possibility of their success and to be
acknowledged about the public motivations to select them. In this paper, we
provide a general schematic of the architecture of participation anticipating
system in preside... | computer science |
40,949 | Data mining application for cyber space users tendency in blog writing:
a case study | cs.CY | Blogs are the recent emerging media which relies on information technology
and technological advance. Since the mass media in some less-developed and
developing countries are in government service and their policies are developed
based on governmental interests, so blogs are provided for ideas and exchanging
opinions. ... | computer science |
40,950 | A Study on Classification in Imbalanced and Partially-Labelled Data
Streams | cs.LG | The domain of radio astronomy is currently facing significant computational
challenges, foremost amongst which are those posed by the development of the
world's largest radio telescope, the Square Kilometre Array (SKA). Preliminary
specifications for this instrument suggest that the final design will
incorporate betwee... | computer science |
40,951 | Multiple Kernel Learning in the Primal for Multi-modal Alzheimer's
Disease Classification | cs.LG | To achieve effective and efficient detection of Alzheimer's disease (AD),
many machine learning methods have been introduced into this realm. However,
the general case of limited training samples, as well as different feature
representations typically makes this problem challenging. In this work, we
propose a novel mul... | computer science |
40,952 | MINT: Mutual Information based Transductive Feature Selection for
Genetic Trait Prediction | cs.LG | Whole genome prediction of complex phenotypic traits using high-density
genotyping arrays has attracted a great deal of attention, as it is relevant to
the fields of plant and animal breeding and genetic epidemiology. As the number
of genotypes is generally much bigger than the number of samples, predictive
models suff... | computer science |
40,953 | Predicting Students' Performance Using ID3 And C4.5 Classification
Algorithms | cs.CY | An educational institution needs to have an approximate prior knowledge of
enrolled students to predict their performance in future academics. This helps
them to identify promising students and also provides them an opportunity to
pay attention to and improve those who would probably get lower grades. As a
solution, we... | computer science |
40,954 | Bandits with Switching Costs: T^{2/3} Regret | cs.LG | We study the adversarial multi-armed bandit problem in a setting where the
player incurs a unit cost each time he switches actions. We prove that the
player's $T$-round minimax regret in this setting is
$\widetilde{\Theta}(T^{2/3})$, thereby closing a fundamental gap in our
understanding of learning with bandit feedbac... | computer science |
40,955 | Joint Indoor Localization and Radio Map Construction with Limited
Deployment Load | cs.NI | One major bottleneck in the practical implementation of received signal
strength (RSS) based indoor localization systems is the extensive deployment
efforts required to construct the radio maps through fingerprinting. In this
paper, we aim to design an indoor localization scheme that can be directly
employed without bu... | computer science |
40,956 | An Extreme Learning Machine Approach to Predicting Near Chaotic HCCI
Combustion Phasing in Real-Time | cs.LG | Fuel efficient Homogeneous Charge Compression Ignition (HCCI) engine
combustion timing predictions must contend with non-linear chemistry,
non-linear physics, period doubling bifurcation(s), turbulent mixing, model
parameters that can drift day-to-day, and air-fuel mixture state information
that cannot typically be res... | computer science |
40,957 | Predicting college basketball match outcomes using machine learning
techniques: some results and lessons learned | cs.LG | Most existing work on predicting NCAAB matches has been developed in a
statistical context. Trusting the capabilities of ML techniques, particularly
classification learners, to uncover the importance of features and learn their
relationships, we evaluated a number of different paradigms on this task. In
this paper, we ... | computer science |
40,958 | Exact Learning of RNA Energy Parameters From Structure | cs.LG | We consider the problem of exact learning of parameters of a linear RNA
energy model from secondary structure data. A necessary and sufficient
condition for learnability of parameters is derived, which is based on
computing the convex hull of union of translated Newton polytopes of input
sequences. The set of learned e... | computer science |
40,959 | On Measure Concentration of Random Maximum A-Posteriori Perturbations | cs.LG | The maximum a-posteriori (MAP) perturbation framework has emerged as a useful
approach for inference and learning in high dimensional complex models. By
maximizing a randomly perturbed potential function, MAP perturbations generate
unbiased samples from the Gibbs distribution. Unfortunately, the computational
cost of g... | computer science |
40,960 | The BeiHang Keystroke Dynamics Authentication System | cs.CR | Keystroke Dynamics is an important biometric solution for person
authentication. Based upon keystroke dynamics, this paper designs an embedded
password protection device, develops an online system, collects two public
databases for promoting the research on keystroke authentication, exploits the
Gabor filter bank to ch... | computer science |
40,961 | Multiple Attractor Cellular Automata (MACA) for Addressing Major
Problems in Bioinformatics | cs.CE | CA has grown as potential classifier for addressing major problems in
bioinformatics. Lot of bioinformatics problems like predicting the protein
coding region, finding the promoter region, predicting the structure of protein
and many other problems in bioinformatics can be addressed through Cellular
Automata. Even thou... | computer science |
40,962 | Reinforcement Learning Framework for Opportunistic Routing in WSNs | cs.NI | Routing packets opportunistically is an essential part of multihop ad hoc
wireless sensor networks. The existing routing techniques are not adaptive
opportunistic. In this paper we have proposed an adaptive opportunistic routing
scheme that routes packets opportunistically in order to ensure that packet
loss is avoided... | computer science |
40,963 | A Parallel SGD method with Strong Convergence | cs.LG | This paper proposes a novel parallel stochastic gradient descent (SGD) method
that is obtained by applying parallel sets of SGD iterations (each set
operating on one node using the data residing in it) for finding the direction
in each iteration of a batch descent method. The method has strong convergence
properties. E... | computer science |
40,964 | Optimization, Learning, and Games with Predictable Sequences | cs.LG | We provide several applications of Optimistic Mirror Descent, an online
learning algorithm based on the idea of predictable sequences. First, we
recover the Mirror Prox algorithm for offline optimization, prove an extension
to Holder-smooth functions, and apply the results to saddle-point type
problems. Next, we prove ... | computer science |
40,965 | From average case complexity to improper learning complexity | cs.LG | The basic problem in the PAC model of computational learning theory is to
determine which hypothesis classes are efficiently learnable. There is
presently a dearth of results showing hardness of learning problems. Moreover,
the existing lower bounds fall short of the best known algorithms.
The biggest challenge in pr... | computer science |
40,966 | The Noisy Power Method: A Meta Algorithm with Applications | cs.DS | We provide a new robust convergence analysis of the well-known power method
for computing the dominant singular vectors of a matrix that we call the noisy
power method. Our result characterizes the convergence behavior of the
algorithm when a significant amount noise is introduced after each
matrix-vector multiplicatio... | computer science |
40,967 | Spectral Clustering via the Power Method -- Provably | cs.LG | Spectral clustering is one of the most important algorithms in data mining
and machine intelligence; however, its computational complexity limits its
application to truly large scale data analysis. The computational bottleneck in
spectral clustering is computing a few of the top eigenvectors of the
(normalized) Laplaci... | computer science |
40,968 | Scalable Influence Estimation in Continuous-Time Diffusion Networks | cs.SI | If a piece of information is released from a media site, can it spread, in 1
month, to a million web pages? This influence estimation problem is very
challenging since both the time-sensitive nature of the problem and the issue
of scalability need to be addressed simultaneously. In this paper, we propose a
randomized a... | computer science |
40,969 | Extended Formulations for Online Linear Bandit Optimization | cs.LG | On-line linear optimization on combinatorial action sets (d-dimensional
actions) with bandit feedback, is known to have complexity in the order of the
dimension of the problem. The exponential weighted strategy achieves the best
known regret bound that is of the order of $d^{2}\sqrt{n}$ (where $d$ is the
dimension of t... | computer science |
40,970 | Recommending with an Agenda: Active Learning of Private Attributes using
Matrix Factorization | cs.LG | Recommender systems leverage user demographic information, such as age,
gender, etc., to personalize recommendations and better place their targeted
ads. Oftentimes, users do not volunteer this information due to privacy
concerns, or due to a lack of initiative in filling out their online profiles.
We illustrate a new ... | computer science |
40,971 | Learning Prices for Repeated Auctions with Strategic Buyers | cs.LG | Inspired by real-time ad exchanges for online display advertising, we
consider the problem of inferring a buyer's value distribution for a good when
the buyer is repeatedly interacting with a seller through a posted-price
mechanism. We model the buyer as a strategic agent, whose goal is to maximize
her long-term surplu... | computer science |
40,972 | Analysis of Distributed Stochastic Dual Coordinate Ascent | cs.DC | In \citep{Yangnips13}, the author presented distributed stochastic dual
coordinate ascent (DisDCA) algorithms for solving large-scale regularized loss
minimization. Extraordinary performances have been observed and reported for
the well-motivated updates, as referred to the practical updates, compared to
the naive upda... | computer science |
40,973 | Bandits and Experts 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 |
40,974 | A MapReduce based distributed SVM algorithm for binary classification | cs.LG | Although Support Vector Machine (SVM) algorithm has a high generalization
property to classify for unseen examples after training phase and it has small
loss value, the algorithm is not suitable for real-life classification and
regression problems. SVMs cannot solve hundreds of thousands examples in
training dataset. I... | computer science |
40,975 | Distributed k-means algorithm | cs.LG | In this paper we provide a fully distributed implementation of the k-means
clustering algorithm, intended for wireless sensor networks where each agent is
endowed with a possibly high-dimensional observation (e.g., position, humidity,
temperature, etc.) The proposed algorithm, by means of one-hop communication,
partiti... | computer science |
40,976 | Classification of Human Ventricular Arrhythmia in High Dimensional
Representation Spaces | cs.CE | We studied classification of human ECGs labelled as normal sinus rhythm,
ventricular fibrillation and ventricular tachycardia by means of support vector
machines in different representation spaces, using different observation
lengths. ECG waveform segments of duration 0.5-4 s, their Fourier magnitude
spectra, and lower... | computer science |
40,977 | Manifold regularized kernel logistic regression for web image annotation | cs.LG | With the rapid advance of Internet technology and smart devices, users often
need to manage large amounts of multimedia information using smart devices,
such as personal image and video accessing and browsing. These requirements
heavily rely on the success of image (video) annotation, and thus large scale
image annotat... | computer science |
40,978 | Co-Multistage of Multiple Classifiers for Imbalanced Multiclass Learning | cs.LG | In this work, we propose two stochastic architectural models (CMC and CMC-M)
with two layers of classifiers applicable to datasets with one and multiple
skewed classes. This distinction becomes important when the datasets have a
large number of classes. Therefore, we present a novel solution to imbalanced
multiclass le... | computer science |
40,979 | Local algorithms for interactive clustering | cs.DS | We study the design of interactive clustering algorithms for data sets
satisfying natural stability assumptions. Our algorithms start with any initial
clustering and only make local changes in each step; both are desirable
features in many applications. We show that in this constrained setting one can
still design prov... | computer science |
40,980 | Greedy Column Subset Selection for Large-scale Data Sets | cs.DS | In today's information systems, the availability of massive amounts of data
necessitates the development of fast and accurate algorithms to summarize these
data and represent them in a succinct format. One crucial problem in big data
analytics is the selection of representative instances from large and
massively-distri... | computer science |
40,981 | Matrix recovery using Split Bregman | cs.NA | In this paper we address the problem of recovering a matrix, with inherent
low rank structure, from its lower dimensional projections. This problem is
frequently encountered in wide range of areas including pattern recognition,
wireless sensor networks, control systems, recommender systems, image/video
reconstruction e... | computer science |
40,982 | Two Timescale Convergent Q-learning for Sleep--Scheduling in Wireless
Sensor Networks | cs.SY | In this paper, we consider an intrusion detection application for Wireless
Sensor Networks (WSNs). We study the problem of scheduling the sleep times of
the individual sensors to maximize the network lifetime while keeping the
tracking error to a minimum. We formulate this problem as a
partially-observable Markov decis... | computer science |
40,983 | Nonparametric Inference For Density Modes | stat.ME | We derive nonparametric confidence intervals for the eigenvalues of the
Hessian at modes of a density estimate. This provides information about the
strength and shape of modes and can also be used as a significance test. We use
a data-splitting approach in which potential modes are identified using the
first half of th... | computer science |
40,984 | Response-Based Approachability and its Application to Generalized
No-Regret Algorithms | cs.LG | Approachability theory, introduced by Blackwell (1956), provides fundamental
results on repeated games with vector-valued payoffs, and has been usefully
applied since in the theory of learning in games and to learning algorithms in
the online adversarial setup. Given a repeated game with vector payoffs, a
target set $S... | computer science |
40,985 | Household Electricity Demand Forecasting -- Benchmarking
State-of-the-Art Methods | cs.LG | The increasing use of renewable energy sources with variable output, such as
solar photovoltaic and wind power generation, calls for Smart Grids that
effectively manage flexible loads and energy storage. The ability to forecast
consumption at different locations in distribution systems will be a key
capability of Smart... | computer science |
40,986 | Learning Two-input Linear and Nonlinear Analog Functions with a Simple
Chemical System | cs.LG | The current biochemical information processing systems behave in a
predetermined manner because all features are defined during the design phase.
To make such unconventional computing systems reusable and programmable for
biomedical applications, adaptation, learning, and self-modification based on
external stimuli wou... | computer science |
40,987 | Cellular Automata and Its Applications in Bioinformatics: A Review | cs.CE | This paper aims at providing a survey on the problems that can be easily
addressed by cellular automata in bioinformatics. Some of the authors have
proposed algorithms for addressing some problems in bioinformatics but the
application of cellular automata in bioinformatics is a virgin field in
research. None of the res... | computer science |
40,988 | piCholesky: Polynomial Interpolation of Multiple Cholesky Factors for
Efficient Approximate Cross-Validation | cs.LG | The dominant cost in solving least-square problems using Newton's method is
often that of factorizing the Hessian matrix over multiple values of the
regularization parameter ($\lambda$). We propose an efficient way to
interpolate the Cholesky factors of the Hessian matrix computed over a small
set of $\lambda$ values. ... | computer science |
40,989 | AIS-MACA- Z: MACA based Clonal Classifier for Splicing Site, Protein
Coding and Promoter Region Identification in Eukaryotes | cs.CE | Bioinformatics incorporates information regarding biological data storage,
accessing mechanisms and presentation of characteristics within this data. Most
of the problems in bioinformatics and be addressed efficiently by computer
techniques. This paper aims at building a classifier based on Multiple
Attractor Cellular ... | computer science |
40,990 | Optimistic Risk Perception in the Temporal Difference error Explains the
Relation between Risk-taking, Gambling, Sensation-seeking and Low Fear | cs.LG | Understanding the affective, cognitive and behavioural processes involved in
risk taking is essential for treatment and for setting environmental conditions
to limit damage. Using Temporal Difference Reinforcement Learning (TDRL) we
computationally investigated the effect of optimism in risk perception in a
variety of ... | computer science |
40,991 | Towards the Safety of Human-in-the-Loop Robotics: Challenges and
Opportunities for Safety Assurance of Robotic Co-Workers | cs.RO | The success of the human-robot co-worker team in a flexible manufacturing
environment where robots learn from demonstration heavily relies on the correct
and safe operation of the robot. How this can be achieved is a challenge that
requires addressing both technical as well as human-centric research questions.
In this ... | computer science |
40,992 | Near-optimal sample compression for nearest neighbors | cs.LG | We present the first sample compression algorithm for nearest neighbors with
non-trivial performance guarantees. We complement these guarantees by
demonstrating almost matching hardness lower bounds, which show that our bound
is nearly optimal. Our result yields new insight into margin-based nearest
neighbor classifica... | computer science |
40,993 | Complexity theoretic limitations on learning DNF's | cs.LG | Using the recently developed framework of [Daniely et al, 2014], we show that
under a natural assumption on the complexity of refuting random K-SAT formulas,
learning DNF formulas is hard. Furthermore, the same assumption implies the
hardness of learning intersections of $\omega(\log(n))$ halfspaces,
agnostically learn... | computer science |
40,994 | Methods for Ordinal Peer Grading | cs.LG | MOOCs have the potential to revolutionize higher education with their wide
outreach and accessibility, but they require instructors to come up with
scalable alternates to traditional student evaluation. Peer grading -- having
students assess each other -- is a promising approach to tackling the problem
of evaluation at... | computer science |
40,995 | Nearly Tight Bounds on $\ell_1$ Approximation of Self-Bounding Functions | cs.LG | We study the complexity of learning and approximation of self-bounding
functions over the uniform distribution on the Boolean hypercube ${0,1}^n$.
Informally, a function $f:{0,1}^n \rightarrow \mathbb{R}$ is self-bounding if
for every $x \in {0,1}^n$, $f(x)$ upper bounds the sum of all the $n$ marginal
decreases in the... | computer science |
40,996 | Concurrent bandits and cognitive radio networks | cs.LG | We consider the problem of multiple users targeting the arms of a single
multi-armed stochastic bandit. The motivation for this problem comes from
cognitive radio networks, where selfish users need to coexist without any side
communication between them, implicit cooperation or common control. Even the
number of users m... | computer science |
40,997 | A Comparison of Clustering and Missing Data Methods for Health Sciences | math.NA | In this paper, we compare and analyze clustering methods with missing data in
health behavior research. In particular, we propose and analyze the use of
compressive sensing's matrix completion along with spectral clustering to
cluster health related data. The empirical tests and real data results show
that these method... | computer science |
40,999 | A Multi Level Data Fusion Approach for Speaker Identification on
Telephone Speech | cs.SD | Several speaker identification systems are giving good performance with clean
speech but are affected by the degradations introduced by noisy audio
conditions. To deal with this problem, we investigate the use of complementary
information at different levels for computing a combined match score for the
unknown speaker.... | computer science |
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