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40,710 | An Initial Seed Selection Algorithm for K-means Clustering of
Georeferenced Data to Improve Replicability of Cluster Assignments for
Mapping Application | cs.LG | K-means is one of the most widely used clustering algorithms in various
disciplines, especially for large datasets. However the method is known to be
highly sensitive to initial seed selection of cluster centers. K-means++ has
been proposed to overcome this problem and has been shown to have better
accuracy and computa... | computer science |
40,711 | CT-Mapper: Mapping Sparse Multimodal Cellular Trajectories using a
Multilayer Transportation Network | cs.SI | Mobile phone data have recently become an attractive source of information
about mobility behavior. Since cell phone data can be captured in a passive way
for a large user population, they can be harnessed to collect well-sampled
mobility information. In this paper, we propose CT-Mapper, an unsupervised
algorithm that ... | computer science |
40,712 | Observing and Recommending from a Social Web with Biases | cs.DB | The research question this report addresses is: how, and to what extent,
those directly involved with the design, development and employment of a
specific black box algorithm can be certain that it is not unlawfully
discriminating (directly and/or indirectly) against particular persons with
protected characteristics (e... | computer science |
40,713 | Unbiased Comparative Evaluation of Ranking Functions | cs.IR | Eliciting relevance judgments for ranking evaluation is labor-intensive and
costly, motivating careful selection of which documents to judge. Unlike
traditional approaches that make this selection deterministically,
probabilistic sampling has shown intriguing promise since it enables the design
of estimators that are p... | computer science |
40,714 | Towards Reduced Reference Parametric Models for Estimating Audiovisual
Quality in Multimedia Services | cs.MM | We have developed reduced reference parametric models for estimating
perceived quality in audiovisual multimedia services. We have created 144
unique configurations for audiovisual content including various application and
network parameters such as bitrates and distortions in terms of bandwidth,
packet loss rate and j... | computer science |
40,715 | Convolutional Neural Networks For Automatic State-Time Feature
Extraction in Reinforcement Learning Applied to Residential Load Control | cs.LG | Direct load control of a heterogeneous cluster of residential demand
flexibility sources is a high-dimensional control problem with partial
observability. This work proposes a novel approach that uses a convolutional
neural network to extract hidden state-time features to mitigate the curse of
partial observability. Mo... | computer science |
40,716 | Detection of epileptic seizure in EEG signals using linear least squares
preprocessing | cs.LG | An epileptic seizure is a transient event of abnormal excessive neuronal
discharge in the brain. This unwanted event can be obstructed by detection of
electrical changes in the brain that happen before the seizure takes place. The
automatic detection of seizures is necessary since the visual screening of EEG
recordings... | computer science |
40,717 | A movie genre prediction based on Multivariate Bernoulli model and genre
correlations | cs.IR | Movie ratings play an important role both in determining the likelihood of a
potential viewer to watch the movie and in reflecting the current viewer
satisfaction with the movie. They are available in several sources like the
television guide, best-selling reference books, newspaper columns, and
television programs. Fu... | computer science |
40,718 | Music transcription modelling and composition using deep learning | cs.SD | We apply deep learning methods, specifically long short-term memory (LSTM)
networks, to music transcription modelling and composition. We build and train
LSTM networks using approximately 23,000 music transcriptions expressed with a
high-level vocabulary (ABC notation), and use them to generate new
transcriptions. Our ... | computer science |
40,719 | Joint Sound Source Separation and Speaker Recognition | cs.SD | Non-negative Matrix Factorization (NMF) has already been applied to learn
speaker characterizations from single or non-simultaneous speech for speaker
recognition applications. It is also known for its good performance in (blind)
source separation for simultaneous speech. This paper explains how NMF can be
used to join... | computer science |
40,720 | A game-theoretic version of Oakes' example for randomized forecasting | cs.LG | Using the game-theoretic framework for probability, Vovk and Shafer. have
shown that it is always possible, using randomization, to make sequential
probability forecasts that pass any countable set of well-behaved statistical
tests. This result generalizes work by other authors, who consider only tests
of calbration.
... | computer science |
40,721 | Craniofacial reconstruction as a prediction problem using a Latent Root
Regression model | cs.LG | In this paper, we present a computer-assisted method for facial
reconstruction. This method provides an estimation of the facial shape
associated with unidentified skeletal remains. Current computer-assisted
methods using a statistical framework rely on a common set of extracted points
located on the bone and soft-tiss... | computer science |
40,722 | Near-optimal Coresets For Least-Squares Regression | cs.DS | We study (constrained) least-squares regression as well as multiple response
least-squares regression and ask the question of whether a subset of the data,
a coreset, suffices to compute a good approximate solution to the regression.
We give deterministic, low order polynomial-time algorithms to construct such
coresets... | computer science |
40,723 | Finding a most biased coin with fewest flips | cs.DS | We study the problem of learning a most biased coin among a set of coins by
tossing the coins adaptively. The goal is to minimize the number of tosses
until we identify a coin i* whose posterior probability of being most biased is
at least 1-delta for a given delta. Under a particular probabilistic model, we
give an op... | computer science |
40,724 | Guaranteed clustering and biclustering via semidefinite programming | math.OC | Identifying clusters of similar objects in data plays a significant role in a
wide range of applications. As a model problem for clustering, we consider the
densest k-disjoint-clique problem, whose goal is to identify the collection of
k disjoint cliques of a given weighted complete graph maximizing the sum of the
dens... | computer science |
40,725 | The best of both worlds: stochastic and adversarial bandits | cs.LG | We present a new bandit algorithm, SAO (Stochastic and Adversarial Optimal),
whose regret is, essentially, optimal both for adversarial rewards and for
stochastic rewards. Specifically, SAO combines the square-root worst-case
regret of Exp3 (Auer et al., SIAM J. on Computing 2002) and the
(poly)logarithmic regret of UC... | computer science |
40,726 | Min Max Generalization for Two-stage Deterministic Batch Mode
Reinforcement Learning: Relaxation Schemes | cs.SY | We study the minmax optimization problem introduced in [22] for computing
policies for batch mode reinforcement learning in a deterministic setting.
First, we show that this problem is NP-hard. In the two-stage case, we provide
two relaxation schemes. The first relaxation scheme works by dropping some
constraints in or... | computer science |
40,727 | Nonlinear Laplacian spectral analysis: Capturing intermittent and
low-frequency spatiotemporal patterns in high-dimensional data | cs.LG | We present a technique for spatiotemporal data analysis called nonlinear
Laplacian spectral analysis (NLSA), which generalizes singular spectrum
analysis (SSA) to take into account the nonlinear manifold structure of complex
data sets. The key principle underlying NLSA is that the functions used to
represent temporal p... | computer science |
40,728 | A Stochastic Gradient Method with an Exponential Convergence Rate for
Finite Training Sets | math.OC | We propose a new stochastic gradient method for optimizing the sum of a
finite set of smooth functions, where the sum is strongly convex. While
standard stochastic gradient methods converge at sublinear rates for this
problem, the proposed method incorporates a memory of previous gradient values
in order to achieve a l... | computer science |
40,729 | A Route Confidence Evaluation Method for Reliable Hierarchical Text
Categorization | cs.IR | Hierarchical Text Categorization (HTC) is becoming increasingly important
with the rapidly growing amount of text data available in the World Wide Web.
Among the different strategies proposed to cope with HTC, the Local Classifier
per Node (LCN) approach attains good performance by mirroring the underlying
class hierar... | computer science |
40,730 | A Machine Learning Approach For Opinion Holder Extraction In Arabic
Language | cs.IR | Opinion mining aims at extracting useful subjective information from reliable
amounts of text. Opinion mining holder recognition is a task that has not been
considered yet in Arabic Language. This task essentially requires deep
understanding of clauses structures. Unfortunately, the lack of a robust,
publicly available... | computer science |
40,731 | Memory-Efficient Topic Modeling | cs.LG | As one of the simplest probabilistic topic modeling techniques, latent
Dirichlet allocation (LDA) has found many important applications in text
mining, computer vision and computational biology. Recent training algorithms
for LDA can be interpreted within a unified message passing framework. However,
message passing re... | computer science |
40,732 | PRISMA: PRoximal Iterative SMoothing Algorithm | math.OC | Motivated by learning problems including max-norm regularized matrix
completion and clustering, robust PCA and sparse inverse covariance selection,
we propose a novel optimization algorithm for minimizing a convex objective
which decomposes into three parts: a smooth part, a simple non-smooth Lipschitz
part, and a simp... | computer science |
40,733 | Sparse Distributed Learning Based on Diffusion Adaptation | cs.LG | This article proposes diffusion LMS strategies for distributed estimation
over adaptive networks that are able to exploit sparsity in the underlying
system model. The approach relies on convex regularization, common in
compressive sensing, to enhance the detection of sparsity via a diffusive
process over the network. T... | computer science |
40,734 | Improved Spectral-Norm Bounds for Clustering | cs.LG | Aiming to unify known results about clustering mixtures of distributions
under separation conditions, Kumar and Kannan[2010] introduced a deterministic
condition for clustering datasets. They showed that this single deterministic
condition encompasses many previously studied clustering assumptions. More
specifically, t... | computer science |
40,735 | A Novel Approach for Protein Structure Prediction | cs.LG | The idea of this project is to study the protein structure and sequence
relationship using the hidden markov model and artificial neural network. In
this context we have assumed two hidden markov models. In first model we have
taken protein secondary structures as hidden and protein sequences as observed.
In second mod... | computer science |
40,736 | Unsupervised adaptation of brain machine interface decoders | cs.LG | The performance of neural decoders can degrade over time due to
nonstationarities in the relationship between neuronal activity and behavior.
In this case, brain-machine interfaces (BMI) require adaptation of their
decoders to maintain high performance across time. One way to achieve this is
by use of periodical calibr... | computer science |
40,737 | ConeRANK: Ranking as Learning Generalized Inequalities | cs.LG | We propose a new data mining approach in ranking documents based on the
concept of cone-based generalized inequalities between vectors. A partial
ordering between two vectors is made with respect to a proper cone and thus
learning the preferences is formulated as learning proper cones. A pairwise
learning-to-rank algor... | computer science |
40,738 | Parsimonious Mahalanobis Kernel for the Classification of High
Dimensional Data | cs.NA | The classification of high dimensional data with kernel methods is considered
in this article. Exploit- ing the emptiness property of high dimensional
spaces, a kernel based on the Mahalanobis distance is proposed. The computation
of the Mahalanobis distance requires the inversion of a covariance matrix. In
high dimens... | computer science |
40,739 | Projection-free Online Learning | cs.LG | The computational bottleneck in applying online learning to massive data sets
is usually the projection step. We present efficient online learning algorithms
that eschew projections in favor of much more efficient linear optimization
steps using the Frank-Wolfe technique. We obtain a range of regret bounds for
online c... | computer science |
40,740 | Provable ICA with Unknown Gaussian Noise, and Implications for Gaussian
Mixtures and Autoencoders | cs.LG | We present a new algorithm for Independent Component Analysis (ICA) which has
provable performance guarantees. In particular, suppose we are given samples of
the form $y = Ax + \eta$ where $A$ is an unknown $n \times n$ matrix and $x$ is
a random variable whose components are independent and have a fourth moment
strict... | computer science |
40,741 | Discrete Elastic Inner Vector Spaces with Application in Time Series and
Sequence Mining | cs.LG | This paper proposes a framework dedicated to the construction of what we call
discrete elastic inner product allowing one to embed sets of non-uniformly
sampled multivariate time series or sequences of varying lengths into inner
product space structures. This framework is based on a recursive definition
that covers the... | computer science |
40,742 | Sequential Document Representations and Simplicial Curves | cs.IR | The popular bag of words assumption represents a document as a histogram of
word occurrences. While computationally efficient, such a representation is
unable to maintain any sequential information. We present a continuous and
differentiable sequential document representation that goes beyond the bag of
words assumptio... | computer science |
40,743 | Distributed Adaptive Networks: A Graphical Evolutionary Game-Theoretic
View | cs.GT | Distributed adaptive filtering has been considered as an effective approach
for data processing and estimation over distributed networks. Most existing
distributed adaptive filtering algorithms focus on designing different
information diffusion rules, regardless of the nature evolutionary
characteristic of a distribute... | computer science |
40,744 | Learning Mixtures of Arbitrary Distributions over Large Discrete Domains | cs.LG | We give an algorithm for learning a mixture of {\em unstructured}
distributions. This problem arises in various unsupervised learning scenarios,
for example in learning {\em topic models} from a corpus of documents spanning
several topics. We show how to learn the constituents of a mixture of $k$
arbitrary distribution... | computer science |
40,745 | Mining Techniques in Network Security to Enhance Intrusion Detection
Systems | cs.CR | In intrusion detection systems, classifiers still suffer from several
drawbacks such as data dimensionality and dominance, different network feature
types, and data impact on the classification. In this paper two significant
enhancements are presented to solve these drawbacks. The first enhancement is
an improved featu... | computer science |
40,746 | Efficient Gradient Estimation for Motor Control Learning | cs.LG | The task of estimating the gradient of a function in the presence of noise is
central to several forms of reinforcement learning, including policy search
methods. We present two techniques for reducing gradient estimation errors in
the presence of observable input noise applied to the control signal. The first
method e... | computer science |
40,747 | Know Your Personalization: Learning Topic level Personalization in
Online Services | cs.LG | Online service platforms (OSPs), such as search engines, news-websites,
ad-providers, etc., serve highly pe rsonalized content to the user, based on
the profile extracted from his history with the OSP. Although personalization
(generally) leads to a better user experience, it also raises privacy concerns
for the user--... | computer science |
40,748 | A metric for software vulnerabilities classification | cs.SE | Vulnerability discovery and exploits detection are two wide areas of study in
software engineering. This preliminary work tries to combine existing methods
with machine learning techniques to define a metric classification of
vulnerable computer programs. First a feature set has been defined and later
two models have b... | computer science |
40,749 | Maximally Informative Observables and Categorical Perception | cs.LG | We formulate the problem of perception in the framework of information
theory, and prove that categorical perception is equivalent to the existence of
an observable that has the maximum possible information on the target of
perception. We call such an observable maximally informative. Regardless
whether categorical per... | computer science |
40,750 | Fuzzy soft rough K-Means clustering approach for gene expression data | cs.LG | Clustering is one of the widely used data mining techniques for medical
diagnosis. Clustering can be considered as the most important unsupervised
learning technique. Most of the clustering methods group data based on distance
and few methods cluster data based on similarity. The clustering algorithms
classify gene exp... | computer science |
40,751 | Soft Set Based Feature Selection Approach for Lung Cancer Images | cs.LG | Lung cancer is the deadliest type of cancer for both men and women. Feature
selection plays a vital role in cancer classification. This paper investigates
the feature selection process in Computed Tomographic (CT) lung cancer images
using soft set theory. We propose a new soft set based unsupervised feature
selection a... | computer science |
40,752 | Reinforcement learning for port-Hamiltonian systems | cs.SY | Passivity-based control (PBC) for port-Hamiltonian systems provides an
intuitive way of achieving stabilization by rendering a system passive with
respect to a desired storage function. However, in most instances the control
law is obtained without any performance considerations and it has to be
calculated by solving a... | computer science |
40,753 | Transfer Learning Using Logistic Regression in Credit Scoring | cs.LG | The credit scoring risk management is a fast growing field due to consumer's
credit requests. Credit requests, of new and existing customers, are often
evaluated by classical discrimination rules based on customers information.
However, these kinds of strategies have serious limits and don't take into
account the chara... | computer science |
40,754 | Fast Solutions to Projective Monotone Linear Complementarity Problems | cs.LG | We present a new interior-point potential-reduction algorithm for solving
monotone linear complementarity problems (LCPs) that have a particular special
structure: their matrix $M\in{\mathbb R}^{n\times n}$ can be decomposed as
$M=\Phi U + \Pi_0$, where the rank of $\Phi$ is $k<n$, and $\Pi_0$ denotes
Euclidean project... | computer science |
40,755 | A Polynomial Time Algorithm for Lossy Population Recovery | cs.DS | We give a polynomial time algorithm for the lossy population recovery
problem. In this problem, the goal is to approximately learn an unknown
distribution on binary strings of length $n$ from lossy samples: for some
parameter $\mu$ each coordinate of the sample is preserved with probability
$\mu$ and otherwise is repla... | computer science |
40,756 | Prediction and Clustering in Signed Networks: A Local to Global
Perspective | cs.SI | The study of social networks is a burgeoning research area. However, most
existing work deals with networks that simply encode whether relationships
exist or not. In contrast, relationships in signed networks can be positive
("like", "trust") or negative ("dislike", "distrust"). The theory of social
balance shows that ... | computer science |
40,757 | The adaptive Gril estimator with a diverging number of parameters | stat.ME | We consider the problem of variables selection and estimation in linear
regression model in situations where the number of parameters diverges with the
sample size. We propose the adaptive Generalized Ridge-Lasso (\mbox{AdaGril})
which is an extension of the the adaptive Elastic Net. AdaGril incorporates
information re... | computer science |
40,758 | ML4PG in Computer Algebra verification | cs.LO | ML4PG is a machine-learning extension that provides statistical proof hints
during the process of Coq/SSReflect proof development. In this paper, we use
ML4PG to find proof patterns in the CoqEAL library -- a library that was
devised to verify the correctness of Computer Algebra algorithms. In
particular, we use ML4PG ... | computer science |
40,759 | Source Separation using Regularized NMF with MMSE Estimates under GMM
Priors with Online Learning for The Uncertainties | cs.LG | We propose a new method to enforce priors on the solution of the nonnegative
matrix factorization (NMF). The proposed algorithm can be used for denoising or
single-channel source separation (SCSS) applications. The NMF solution is
guided to follow the Minimum Mean Square Error (MMSE) estimates under Gaussian
mixture pr... | computer science |
40,760 | Fast Feature Reduction in intrusion detection datasets | cs.CR | In the most intrusion detection systems (IDS), a system tries to learn
characteristics of different type of attacks by analyzing packets that sent or
received in network. These packets have a lot of features. But not all of them
is required to be analyzed to detect that specific type of attack. Detection
speed and comp... | computer science |
40,761 | Bandits with Knapsacks | cs.DS | Multi-armed bandit problems are the predominant theoretical model of
exploration-exploitation tradeoffs in learning, and they have countless
applications ranging from medical trials, to communication networks, to Web
search and advertising. In many of these application domains the learner may be
constrained by one or m... | computer science |
40,762 | HRF estimation improves sensitivity of fMRI encoding and decoding models | cs.LG | Extracting activation patterns from functional Magnetic Resonance Images
(fMRI) datasets remains challenging in rapid-event designs due to the inherent
delay of blood oxygen level-dependent (BOLD) signal. The general linear model
(GLM) allows to estimate the activation from a design matrix and a fixed
hemodynamic respo... | computer science |
40,763 | Real Time Bid Optimization with Smooth Budget Delivery in Online
Advertising | cs.GT | Today, billions of display ad impressions are purchased on a daily basis
through a public auction hosted by real time bidding (RTB) exchanges. A
decision has to be made for advertisers to submit a bid for each selected RTB
ad request in milliseconds. Restricted by the budget, the goal is to buy a set
of ad impressions ... | computer science |
40,764 | Scalable Audience Reach Estimation in Real-time Online Advertising | cs.LG | Online advertising has been introduced as one of the most efficient methods
of advertising throughout the recent years. Yet, advertisers are concerned
about the efficiency of their online advertising campaigns and consequently,
would like to restrict their ad impressions to certain websites and/or certain
groups of aud... | computer science |
40,765 | Qualitative detection of oil adulteration with machine learning
approaches | cs.CE | The study focused on the machine learning analysis approaches to identify the
adulteration of 9 kinds of edible oil qualitatively and answered the following
three questions: Is the oil sample adulterant? How does it constitute? What is
the main ingredient of the adulteration oil? After extracting the
high-performance l... | computer science |
40,766 | Transfer Learning for Content-Based Recommender Systems using Tree
Matching | cs.LG | In this paper we present a new approach to content-based transfer learning
for solving the data sparsity problem in cases when the users' preferences in
the target domain are either scarce or unavailable, but the necessary
information on the preferences exists in another domain. We show that training
a system to use su... | computer science |
40,767 | Multi-View Learning for Web Spam Detection | cs.IR | Spam pages are designed to maliciously appear among the top search results by
excessive usage of popular terms. Therefore, spam pages should be removed using
an effective and efficient spam detection system. Previous methods for web spam
classification used several features from various information sources (page
conten... | computer science |
40,768 | Generalized Centroid Estimators in Bioinformatics | cs.LG | In a number of estimation problems in bioinformatics, accuracy measures of
the target problem are usually given, and it is important to design estimators
that are suitable to those accuracy measures. However, there is often a
discrepancy between an employed estimator and a given accuracy measure of the
problem. In this... | computer science |
40,769 | Robustness of Random Forest-based gene selection methods | cs.LG | Gene selection is an important part of microarray data analysis because it
provides information that can lead to a better mechanistic understanding of an
investigated phenomenon. At the same time, gene selection is very difficult
because of the noisy nature of microarray data. As a consequence, gene
selection is often ... | computer science |
40,770 | Power to the Points: Validating Data Memberships in Clusterings | cs.LG | A clustering is an implicit assignment of labels of points, based on
proximity to other points. It is these labels that are then used for downstream
analysis (either focusing on individual clusters, or identifying
representatives of clusters and so on). Thus, in order to trust a clustering as
a first step in explorator... | computer science |
40,771 | Zero-sum repeated games: Counterexamples to the existence of the
asymptotic value and the conjecture
$\operatorname{maxmin}=\operatorname{lim}v_n$ | math.OC | Mertens [In Proceedings of the International Congress of Mathematicians
(Berkeley, Calif., 1986) (1987) 1528-1577 Amer. Math. Soc.] proposed two
general conjectures about repeated games: the first one is that, in any
two-person zero-sum repeated game, the asymptotic value exists, and the second
one is that, when Player... | computer science |
40,772 | Supervised Feature Selection for Diagnosis of Coronary Artery Disease
Based on Genetic Algorithm | cs.LG | Feature Selection (FS) has become the focus of much research on decision
support systems areas for which data sets with tremendous number of variables
are analyzed. In this paper we present a new method for the diagnosis of
Coronary Artery Diseases (CAD) founded on Genetic Algorithm (GA) wrapped Bayes
Naive (BN) based ... | computer science |
40,773 | Speeding-Up Convergence via Sequential Subspace Optimization: Current
State and Future Directions | cs.NA | This is an overview paper written in style of research proposal. In recent
years we introduced a general framework for large-scale unconstrained
optimization -- Sequential Subspace Optimization (SESOP) and demonstrated its
usefulness for sparsity-based signal/image denoising, deconvolution,
compressive sensing, compute... | computer science |
40,774 | Robust Hierarchical Clustering | cs.LG | One of the most widely used techniques for data clustering is agglomerative
clustering. Such algorithms have been long used across many different fields
ranging from computational biology to social sciences to computer vision in
part because their output is easy to interpret. Unfortunately, it is well
known, however, t... | computer science |
40,775 | Modeling Attractiveness and Multiple Clicks in Sponsored Search Results | cs.IR | Click models are an important tool for leveraging user feedback, and are used
by commercial search engines for surfacing relevant search results. However,
existing click models are lacking in two aspects. First, they do not share
information across search results when computing attractiveness. Second, they
assume that ... | computer science |
40,776 | Least Squares Policy Iteration with Instrumental Variables vs. Direct
Policy Search: Comparison Against Optimal Benchmarks Using Energy Storage | math.OC | This paper studies approximate policy iteration (API) methods which use
least-squares Bellman error minimization for policy evaluation. We address
several of its enhancements, namely, Bellman error minimization using
instrumental variables, least-squares projected Bellman error minimization, and
projected Bellman error... | computer science |
40,777 | PSMACA: An Automated Protein Structure Prediction Using MACA (Multiple
Attractor Cellular Automata) | cs.CE | Protein Structure Predication from sequences of amino acid has gained a
remarkable attention in recent years. Even though there are some prediction
techniques addressing this problem, the approximate accuracy in predicting the
protein structure is closely 75%. An automated procedure was evolved with MACA
(Multiple Attr... | computer science |
40,778 | Use Case Point Approach Based Software Effort Estimation using Various
Support Vector Regression Kernel Methods | cs.SE | The job of software effort estimation is a critical one in the early stages
of the software development life cycle when the details of requirements are
usually not clearly identified. Various optimization techniques help in
improving the accuracy of effort estimation. The Support Vector Regression
(SVR) is one of sever... | computer science |
40,779 | Infinite Mixed Membership Matrix Factorization | cs.LG | Rating and recommendation systems have become a popular application area for
applying a suite of machine learning techniques. Current approaches rely
primarily on probabilistic interpretations and extensions of matrix
factorization, which factorizes a user-item ratings matrix into latent user and
item vectors. Most of ... | computer science |
40,780 | A Multiagent Reinforcement Learning Algorithm with Non-linear Dynamics | cs.LG | Several multiagent reinforcement learning (MARL) algorithms have been
proposed to optimize agents decisions. Due to the complexity of the problem,
the majority of the previously developed MARL algorithms assumed agents either
had some knowledge of the underlying game (such as Nash equilibria) and/or
observed other agen... | computer science |
40,781 | RoxyBot-06: Stochastic Prediction and Optimization in TAC Travel | cs.GT | In this paper, we describe our autonomous bidding agent, RoxyBot, who emerged
victorious in the travel division of the 2006 Trading Agent Competition in a
photo finish. At a high level, the design of many successful trading agents can
be summarized as follows: (i) price prediction: build a model of market prices;
and (... | computer science |
40,782 | An Active Learning Approach for Jointly Estimating Worker Performance
and Annotation Reliability with Crowdsourced Data | cs.LG | Crowdsourcing platforms offer a practical solution to the problem of
affordably annotating large datasets for training supervised classifiers.
Unfortunately, poor worker performance frequently threatens to compromise
annotation reliability, and requesting multiple labels for every instance can
lead to large cost increa... | computer science |
40,783 | Policy Invariance under Reward Transformations for General-Sum
Stochastic Games | cs.GT | We extend the potential-based shaping method from Markov decision processes
to multi-player general-sum stochastic games. We prove that the Nash equilibria
in a stochastic game remains unchanged after potential-based shaping is applied
to the environment. The property of policy invariance provides a possible way
of spe... | computer science |
40,784 | Towards the selection of patients requiring ICD implantation by
automatic classification from Holter monitoring indices | cs.LG | The purpose of this study is to optimize the selection of prophylactic
cardioverter defibrillator implantation candidates. Currently, the main
criterion for implantation is a low Left Ventricular Ejection Fraction (LVEF)
whose specificity is relatively poor. We designed two classifiers aimed to
predict, from long term ... | computer science |
40,785 | General factorization framework for context-aware recommendations | cs.IR | Context-aware recommendation algorithms focus on refining recommendations by
considering additional information, available to the system. This topic has
gained a lot of attention recently. Among others, several factorization methods
were proposed to solve the problem, although most of them assume explicit
feedback whic... | computer science |
40,786 | miRNA and Gene Expression based Cancer Classification using Self-
Learning and Co-Training Approaches | cs.CE | miRNA and gene expression profiles have been proved useful for classifying
cancer samples. Efficient classifiers have been recently sought and developed.
A number of attempts to classify cancer samples using miRNA/gene expression
profiles are known in literature. However, the use of semi-supervised learning
models have... | computer science |
40,787 | HMACA: Towards Proposing a Cellular Automata Based Tool for Protein
Coding, Promoter Region Identification and Protein Structure Prediction | cs.CE | Human body consists of lot of cells, each cell consist of DeOxaRibo Nucleic
Acid (DNA). Identifying the genes from the DNA sequences is a very difficult
task. But identifying the coding regions is more complex task compared to the
former. Identifying the protein which occupy little place in genes is a really
challengin... | computer science |
40,788 | Numerical weather prediction or stochastic modeling: an objective
criterion of choice for the global radiation forecasting | stat.AP | Numerous methods exist and were developed for global radiation forecasting.
The two most popular types are the numerical weather predictions (NWP) and the
predictions using stochastic approaches. We propose to compute a parameter
noted constructed in part from the mutual information which is a quantity that
measures th... | computer science |
40,789 | Iterative Universal Hash Function Generator for Minhashing | cs.LG | Minhashing is a technique used to estimate the Jaccard Index between two sets
by exploiting the probability of collision in a random permutation. In order to
speed up the computation, a random permutation can be approximated by using an
universal hash function such as the $h_{a,b}$ function proposed by Carter and
Wegma... | computer science |
40,790 | Identification of Protein Coding Regions in Genomic DNA Using
Unsupervised FMACA Based Pattern Classifier | cs.CE | Genes carry the instructions for making proteins that are found in a cell as
a specific sequence of nucleotides that are found in DNA molecules. But, the
regions of these genes that code for proteins may occupy only a small region of
the sequence. Identifying the coding regions play a vital role in understanding
these ... | computer science |
40,791 | Security Evaluation of Support Vector Machines in Adversarial
Environments | cs.LG | Support Vector Machines (SVMs) are among the most popular classification
techniques adopted in security applications like malware detection, intrusion
detection, and spam filtering. However, if SVMs are to be incorporated in
real-world security systems, they must be able to cope with attack patterns
that can either mis... | computer science |
40,792 | Empirically Evaluating Multiagent Learning Algorithms | cs.GT | There exist many algorithms for learning how to play repeated bimatrix games.
Most of these algorithms are justified in terms of some sort of theoretical
guarantee. On the other hand, little is known about the empirical performance
of these algorithms. Most such claims in the literature are based on small
experiments, ... | computer science |
40,793 | Local Gaussian Regression | cs.LG | Locally weighted regression was created as a nonparametric learning method
that is computationally efficient, can learn from very large amounts of data
and add data incrementally. An interesting feature of locally weighted
regression is that it can work with spatially varying length scales, a
beneficial property, for i... | computer science |
40,794 | Localized epidemic detection in networks with overwhelming noise | cs.SI | We consider the problem of detecting an epidemic in a population where
individual diagnoses are extremely noisy. The motivation for this problem is
the plethora of examples (influenza strains in humans, or computer viruses in
smartphones, etc.) where reliable diagnoses are scarce, but noisy data
plentiful. In flu/phone... | computer science |
40,795 | Dictionary Learning over Distributed Models | cs.LG | In this paper, we consider learning dictionary models over a network of
agents, where each agent is only in charge of a portion of the dictionary
elements. This formulation is relevant in Big Data scenarios where large
dictionary models may be spread over different spatial locations and it is not
feasible to aggregate ... | computer science |
40,796 | Characterizing the Sample Complexity of Private Learners | cs.CR | In 2008, Kasiviswanathan et al. defined private learning as a combination of
PAC learning and differential privacy. Informally, a private learner is applied
to a collection of labeled individual information and outputs a hypothesis
while preserving the privacy of each individual. Kasiviswanathan et al. gave a
generic c... | computer science |
40,797 | Computational Limits for Matrix Completion | cs.CC | Matrix Completion is the problem of recovering an unknown real-valued
low-rank matrix from a subsample of its entries. Important recent results show
that the problem can be solved efficiently under the assumption that the
unknown matrix is incoherent and the subsample is drawn uniformly at random.
Are these assumptions... | computer science |
40,798 | Discretization of Temporal Data: A Survey | cs.DB | In real world, the huge amount of temporal data is to be processed in many
application areas such as scientific, financial, network monitoring, sensor
data analysis. Data mining techniques are primarily oriented to handle discrete
features. In the case of temporal data the time plays an important role on the
characteri... | computer science |
40,799 | Diffusion Least Mean Square: Simulations | cs.LG | In this technical report we analyse the performance of diffusion strategies
applied to the Least-Mean-Square adaptive filter. We configure a network of
cooperative agents running adaptive filters and discuss their behaviour when
compared with a non-cooperative agent which represents the average of the
network. The anal... | computer science |
40,800 | Open science in machine learning | cs.LG | We present OpenML and mldata, open science platforms that provides easy
access to machine learning data, software and results to encourage further
study and application. They go beyond the more traditional repositories for
data sets and software packages in that they allow researchers to also easily
share the results t... | computer science |
40,801 | Oracle-Based Robust Optimization via Online Learning | math.OC | Robust optimization is a common framework in optimization under uncertainty
when the problem parameters are not known, but it is rather known that the
parameters belong to some given uncertainty set. In the robust optimization
framework the problem solved is a min-max problem where a solution is judged
according to its... | computer science |
40,802 | Outlier Detection using Improved Genetic K-means | cs.LG | The outlier detection problem in some cases is similar to the classification
problem. For example, the main concern of clustering-based outlier detection
algorithms is to find clusters and outliers, which are often regarded as noise
that should be removed in order to make more reliable clustering. In this
article, we p... | computer science |
40,803 | Data-driven HRF estimation for encoding and decoding models | cs.CE | Despite the common usage of a canonical, data-independent, hemodynamic
response function (HRF), it is known that the shape of the HRF varies across
brain regions and subjects. This suggests that a data-driven estimation of this
function could lead to more statistical power when modeling BOLD fMRI data.
However, unconst... | computer science |
40,804 | Real-time Topic-aware Influence Maximization Using Preprocessing | cs.SI | Influence maximization is the task of finding a set of seed nodes in a social
network such that the influence spread of these seed nodes based on certain
influence diffusion model is maximized. Topic-aware influence diffusion models
have been recently proposed to address the issue that influence between a pair
of users... | computer science |
40,805 | Network Traffic Decomposition for Anomaly Detection | cs.LG | In this paper we focus on the detection of network anomalies like Denial of
Service (DoS) attacks and port scans in a unified manner. While there has been
an extensive amount of research in network anomaly detection, current state of
the art methods are only able to detect one class of anomalies at the cost of
others. ... | computer science |
40,806 | An Extensive Repot on the Efficiency of AIS-INMACA (A Novel Integrated
MACA based Clonal Classifier for Protein Coding and Promoter Region
Prediction) | cs.CE | This paper exclusively reports the efficiency of AIS-INMACA. AIS-INMACA has
created good impact on solving major problems in bioinformatics like protein
region identification and promoter region prediction with less time (Pokkuluri
Kiran Sree, 2014). This AIS-INMACA is now came with several variations
(Pokkuluri Kiran ... | computer science |
40,807 | Statistical Structure Learning, Towards a Robust Smart Grid | cs.LG | Robust control and maintenance of the grid relies on accurate data. Both PMUs
and state estimators are prone to false data injection attacks. Thus, it is
crucial to have a mechanism for fast and accurate detection of an agent
maliciously tampering with the data---for both preventing attacks that may lead
to blackouts, ... | computer science |
40,808 | Combination of PCA with SMOTE Resampling to Boost the Prediction Rate in
Lung Cancer Dataset | cs.LG | Classification algorithms are unable to make reliable models on the datasets
with huge sizes. These datasets contain many irrelevant and redundant features
that mislead the classifiers. Furthermore, many huge datasets have imbalanced
class distribution which leads to bias over majority class in the
classification proce... | computer science |
40,809 | Transfer Learning across Networks for Collective Classification | cs.LG | This paper addresses the problem of transferring useful knowledge from a
source network to predict node labels in a newly formed target network. While
existing transfer learning research has primarily focused on vector-based data,
in which the instances are assumed to be independent and identically
distributed, how to ... | computer science |
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