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40,410 | An Analytical Study on Behavior of Clusters Using K Means, EM and K*
Means Algorithm | cs.LG | Clustering is an unsupervised learning method that constitutes a cornerstone
of an intelligent data analysis process. It is used for the exploration of
inter-relationships among a collection of patterns, by organizing them into
homogeneous clusters. Clustering has been dynamically applied to a variety of
tasks in the f... | computer science |
40,411 | Settling the Polynomial Learnability of Mixtures of Gaussians | cs.LG | Given data drawn from a mixture of multivariate Gaussians, a basic problem is
to accurately estimate the mixture parameters. We give an algorithm for this
problem that has a running time, and data requirement polynomial in the
dimension and the inverse of the desired accuracy, with provably minimal
assumptions on the G... | computer science |
40,412 | Polynomial Learning of Distribution Families | cs.LG | The question of polynomial learnability of probability distributions,
particularly Gaussian mixture distributions, has recently received significant
attention in theoretical computer science and machine learning. However,
despite major progress, the general question of polynomial learnability of
Gaussian mixture distri... | computer science |
40,413 | Machine Learning for Galaxy Morphology Classification | cs.LG | In this work, decision tree learning algorithms and fuzzy inferencing systems
are applied for galaxy morphology classification. In particular, the CART, the
C4.5, the Random Forest and fuzzy logic algorithms are studied and reliable
classifiers are developed to distinguish between spiral galaxies, elliptical
galaxies o... | computer science |
40,414 | Estimating small moments of data stream in nearly optimal space-time | cs.DS | For each $p \in (0,2]$, we present a randomized algorithm that returns an
$\epsilon$-approximation of the $p$th frequency moment of a data stream $F_p =
\sum_{i = 1}^n \abs{f_i}^p$. The algorithm requires space $O(\epsilon^{-2} \log
(mM)(\log n))$ and processes each stream update using time $O((\log n) (\log
\epsilon^{... | computer science |
40,415 | On the Finite Time Convergence of Cyclic Coordinate Descent Methods | cs.LG | Cyclic coordinate descent is a classic optimization method that has witnessed
a resurgence of interest in machine learning. Reasons for this include its
simplicity, speed and stability, as well as its competitive performance on
$\ell_1$ regularized smooth optimization problems. Surprisingly, very little is
known about ... | computer science |
40,416 | A Short Introduction to Model Selection, Kolmogorov Complexity and
Minimum Description Length (MDL) | cs.LG | The concept of overfitting in model selection is explained and demonstrated
with an example. After providing some background information on information
theory and Kolmogorov complexity, we provide a short explanation of Minimum
Description Length and error minimization. We conclude with a discussion of the
typical feat... | computer science |
40,417 | Eigenvectors for clustering: Unipartite, bipartite, and directed graph
cases | cs.LG | This paper presents a concise tutorial on spectral clustering for broad
spectrum graphs which include unipartite (undirected) graph, bipartite graph,
and directed graph. We show how to transform bipartite graph and directed graph
into corresponding unipartite graph, therefore allowing a unified treatment to
all cases. ... | computer science |
40,418 | Structural Drift: The Population Dynamics of Sequential Learning | cs.LG | We introduce a theory of sequential causal inference in which learners in a
chain estimate a structural model from their upstream teacher and then pass
samples from the model to their downstream student. It extends the population
dynamics of genetic drift, recasting Kimura's selectively neutral theory as a
special case... | computer science |
40,419 | On Recursive Edit Distance Kernels with Application to Time Series
Classification | cs.LG | This paper proposes some extensions to the work on kernels dedicated to
string or time series global alignment based on the aggregation of scores
obtained by local alignments. The extensions we propose allow to construct,
from classical recursive definition of elastic distances, recursive edit
distance (or time-warp) k... | computer science |
40,420 | Wirtinger's Calculus in general Hilbert Spaces | cs.LG | The present report, has been inspired by the need of the author and its
colleagues to understand the underlying theory of Wirtinger's Calculus and to
further extend it to include the kernel case. The aim of the present manuscript
is twofold: a) it endeavors to provide a more rigorous presentation of the
related materia... | computer science |
40,421 | Ranked bandits in metric spaces: learning optimally diverse rankings
over large document collections | cs.LG | Most learning to rank research has assumed that the utility of different
documents is independent, which results in learned ranking functions that
return redundant results. The few approaches that avoid this have rather
unsatisfyingly lacked theoretical foundations, or do not scale. We present a
learning-to-rank formul... | computer science |
40,422 | GraphLab: A New Framework for Parallel Machine Learning | cs.LG | Designing and implementing efficient, provably correct parallel machine
learning (ML) algorithms is challenging. Existing high-level parallel
abstractions like MapReduce are insufficiently expressive while low-level tools
like MPI and Pthreads leave ML experts repeatedly solving the same design
challenges. By targeting... | computer science |
40,423 | Data Stream Clustering: Challenges and Issues | cs.DB | Very large databases are required to store massive amounts of data that are
continuously inserted and queried. Analyzing huge data sets and extracting
valuable pattern in many applications are interesting for researchers. We can
identify two main groups of techniques for huge data bases mining. One group
refers to stre... | computer science |
40,424 | A Survey Paper on Recommender Systems | cs.IR | Recommender systems apply data mining techniques and prediction algorithms to
predict users' interest on information, products and services among the
tremendous amount of available items. The vast growth of information on the
Internet as well as number of visitors to websites add some key challenges to
recommender syst... | computer science |
40,425 | The Link Prediction Problem in Bipartite Networks | cs.LG | We define and study the link prediction problem in bipartite networks,
specializing general link prediction algorithms to the bipartite case. In a
graph, a link prediction function of two vertices denotes the similarity or
proximity of the vertices. Common link prediction functions for general graphs
are defined using ... | computer science |
40,426 | Safe Feature Elimination in Sparse Supervised Learning | cs.LG | We investigate fast methods that allow to quickly eliminate variables
(features) in supervised learning problems involving a convex loss function and
a $l_1$-norm penalty, leading to a potentially substantial reduction in the
number of variables prior to running the supervised learning algorithm. The
methods are not he... | computer science |
40,427 | A Fast Audio Clustering Using Vector Quantization and Second Order
Statistics | cs.SD | This paper describes an effective unsupervised speaker indexing approach. We
suggest a two stage algorithm to speed-up the state-of-the-art algorithm based
on the Bayesian Information Criterion (BIC). In the first stage of the merging
process a computationally cheap method based on the vector quantization (VQ) is
used.... | computer science |
40,428 | Speaker Identification using MFCC-Domain Support Vector Machine | cs.LG | Speech recognition and speaker identification are important for
authentication and verification in security purpose, but they are difficult to
achieve. Speaker identification methods can be divided into text-independent
and text-dependent. This paper presents a technique of text-dependent speaker
identification using M... | computer science |
40,429 | Approximate Maximum A Posteriori Inference with Entropic Priors | cs.SD | In certain applications it is useful to fit multinomial distributions to
observed data with a penalty term that encourages sparsity. For example, in
probabilistic latent audio source decomposition one may wish to encode the
assumption that only a few latent sources are active at any given time. The
standard heuristic o... | computer science |
40,430 | Multiarmed Bandit Problems with Delayed Feedback | cs.DS | In this paper we initiate the study of optimization of bandit type problems
in scenarios where the feedback of a play is not immediately known. This arises
naturally in allocation problems which have been studied extensively in the
literature, albeit in the absence of delays in the feedback. We study this
problem in th... | computer science |
40,431 | Blackwell Approachability and Low-Regret Learning are Equivalent | cs.LG | We consider the celebrated Blackwell Approachability Theorem for two-player
games with vector payoffs. We show that Blackwell's result is equivalent, via
efficient reductions, to the existence of "no-regret" algorithms for Online
Linear Optimization. Indeed, we show that any algorithm for one such problem
can be effici... | computer science |
40,432 | Robust Distributed Online Prediction | cs.LG | The standard model of online prediction deals with serial processing of
inputs by a single processor. However, in large-scale online prediction
problems, where inputs arrive at a high rate, an increasingly common necessity
is to distribute the computation across several processors. A non-trivial
challenge is to design ... | computer science |
40,433 | Context Aware End-to-End Connectivity Management | cs.LG | In a dynamic heterogeneous environment, such as pervasive and ubiquitous
computing, context-aware adaptation is a key concept to meet the varying
requirements of different users. Connectivity is an important context source
that can be utilized for optimal management of diverse networking resources.
Application QoS (Qua... | computer science |
40,434 | Refinement of Operator-valued Reproducing Kernels | cs.LG | This paper studies the construction of a refinement kernel for a given
operator-valued reproducing kernel such that the vector-valued reproducing
kernel Hilbert space of the refinement kernel contains that of the given one as
a subspace. The study is motivated from the need of updating the current
operator-valued repro... | computer science |
40,435 | Online Learning of Rested and Restless Bandits | math.OC | In this paper we study the online learning problem involving rested and
restless multiarmed bandits with multiple plays. The system consists of a
single player/user and a set of K finite-state discrete-time Markov chains
(arms) with unknown state spaces and statistics. At each time step the player
can play M arms. The ... | computer science |
40,436 | Privacy Preserving Spam Filtering | cs.LG | Email is a private medium of communication, and the inherent privacy
constraints form a major obstacle in developing effective spam filtering
methods which require access to a large amount of email data belonging to
multiple users. To mitigate this problem, we envision a privacy preserving spam
filtering system, where ... | computer science |
40,437 | Sparse neural networks with large learning diversity | cs.LG | Coded recurrent neural networks with three levels of sparsity are introduced.
The first level is related to the size of messages, much smaller than the
number of available neurons. The second one is provided by a particular coding
rule, acting as a local constraint in the neural activity. The third one is a
characteris... | computer science |
40,438 | Link Prediction by De-anonymization: How We Won the Kaggle Social
Network Challenge | cs.CR | This paper describes the winning entry to the IJCNN 2011 Social Network
Challenge run by Kaggle.com. The goal of the contest was to promote research on
real-world link prediction, and the dataset was a graph obtained by crawling
the popular Flickr social photo sharing website, with user identities scrubbed.
By de-anony... | computer science |
40,439 | Fast and Faster: A Comparison of Two Streamed Matrix Decomposition
Algorithms | cs.NA | With the explosion of the size of digital dataset, the limiting factor for
decomposition algorithms is the \emph{number of passes} over the input, as the
input is often stored out-of-core or even off-site. Moreover, we're only
interested in algorithms that operate in \emph{constant memory} w.r.t. to the
input size, so ... | computer science |
40,440 | Named Entity Recognition Using Web Document Corpus | cs.IR | This paper introduces a named entity recognition approach in textual corpus.
This Named Entity (NE) can be a named: location, person, organization, date,
time, etc., characterized by instances. A NE is found in texts accompanied by
contexts: words that are left or right of the NE. The work mainly aims at
identifying co... | computer science |
40,441 | A Gentle Introduction to the Kernel Distance | cs.CG | This document reviews the definition of the kernel distance, providing a
gentle introduction tailored to a reader with background in theoretical
computer science, but limited exposure to technology more common to machine
learning, functional analysis and geometric measure theory. The key aspect of
the kernel distance d... | computer science |
40,442 | Data-Distributed Weighted Majority and Online Mirror Descent | cs.LG | In this paper, we focus on the question of the extent to which online
learning can benefit from distributed computing. We focus on the setting in
which $N$ agents online-learn cooperatively, where each agent only has access
to its own data. We propose a generic data-distributed online learning
meta-algorithm. We then i... | computer science |
40,443 | A Note on the Entropy/Influence Conjecture | math.CO | The entropy/influence conjecture, raised by Friedgut and Kalai in 1996, seeks
to relate two different measures of concentration of the Fourier coefficients
of a Boolean function. Roughly saying, it claims that if the Fourier spectrum
is "smeared out", then the Fourier coefficients are concentrated on "high"
levels. In ... | computer science |
40,444 | Complexity Analysis of Vario-eta through Structure | cs.LG | Graph-based representations of images have recently acquired an important
role for classification purposes within the context of machine learning
approaches. The underlying idea is to consider that relevant information of an
image is implicitly encoded into the relationships between more basic entities
that compose by ... | computer science |
40,445 | Learning, investments and derivatives | cs.LG | The recent crisis and the following flight to simplicity put most derivative
businesses around the world under considerable pressure. We argue that the
traditional modeling techniques must be extended to include product design. We
propose a quantitative framework for creating products which meet the challenge
of being ... | computer science |
40,446 | Learning XML Twig Queries | cs.DB | We investigate the problem of learning XML queries, path queries and tree
pattern queries, from examples given by the user. A learning algorithm takes on
the input a set of XML documents with nodes annotated by the user and returns a
query that selects the nodes in a manner consistent with the annotation. We
study two ... | computer science |
40,447 | On the Inclusion Relation of Reproducing Kernel Hilbert Spaces | math.FA | To help understand various reproducing kernels used in applied sciences, we
investigate the inclusion relation of two reproducing kernel Hilbert spaces.
Characterizations in terms of feature maps of the corresponding reproducing
kernels are established. A full table of inclusion relations among widely-used
translation ... | computer science |
40,448 | HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient
Descent | math.OC | Stochastic Gradient Descent (SGD) is a popular algorithm that can achieve
state-of-the-art performance on a variety of machine learning tasks. Several
researchers have recently proposed schemes to parallelize SGD, but all require
performance-destroying memory locking and synchronization. This work aims to
show using no... | computer science |
40,449 | Generating a Diverse Set of High-Quality Clusterings | cs.LG | We provide a new framework for generating multiple good quality partitions
(clusterings) of a single data set. Our approach decomposes this problem into
two components, generating many high-quality partitions, and then grouping
these partitions to obtain k representatives. The decomposition makes the
approach extremely... | computer science |
40,450 | Efficient Multicore Collaborative Filtering | cs.LG | This paper describes the solution method taken by LeBuSiShu team for track1
in ACM KDD CUP 2011 contest (resulting in the 5th place). We identified two
main challenges: the unique item taxonomy characteristics as well as the large
data set size.To handle the item taxonomy, we present a novel method called
Matrix Factor... | computer science |
40,451 | The fuzzy gene filter: A classifier performance assesment | cs.LG | The Fuzzy Gene Filter (FGF) is an optimised Fuzzy Inference System designed
to rank genes in order of differential expression, based on expression data
generated in a microarray experiment. This paper examines the effectiveness of
the FGF for feature selection using various classification architectures. The
FGF is comp... | computer science |
40,452 | Improving the performance of the ripper in insurance risk classification
: A comparitive study using feature selection | cs.LG | The Ripper algorithm is designed to generate rule sets for large datasets
with many features. However, it was shown that the algorithm struggles with
classification performance in the presence of missing data. The algorithm
struggles to classify instances when the quality of the data deteriorates as a
result of increas... | computer science |
40,453 | Probability Ranking in Vector Spaces | cs.IR | The Probability Ranking Principle states that the document set with the
highest values of probability of relevance optimizes information retrieval
effectiveness given the probabilities are estimated as accurately as possible.
The key point of the principle is the separation of the document set into two
subsets with a g... | computer science |
40,454 | No Internal Regret via Neighborhood Watch | cs.LG | We present an algorithm which attains O(\sqrt{T}) internal (and thus
external) regret for finite games with partial monitoring under the local
observability condition. Recently, this condition has been shown by (Bartok,
Pal, and Szepesvari, 2011) to imply the O(\sqrt{T}) rate for partial monitoring
games against an i.i... | computer science |
40,455 | Infinite Tucker Decomposition: Nonparametric Bayesian Models for
Multiway Data Analysis | cs.LG | Tensor decomposition is a powerful computational tool for multiway data
analysis. Many popular tensor decomposition approaches---such as the Tucker
decomposition and CANDECOMP/PARAFAC (CP)---amount to multi-linear
factorization. They are insufficient to model (i) complex interactions between
data entities, (ii) various... | computer science |
40,456 | Blackwell Approachability and Minimax Theory | cs.GT | This manuscript investigates the relationship between Blackwell
Approachability, a stochastic vector-valued repeated game, and minimax theory,
a single-play scalar-valued scenario. First, it is established in a general
setting --- one not permitting invocation of minimax theory --- that
Blackwell's Approachability Theo... | computer science |
40,457 | A Study of Unsupervised Adaptive Crowdsourcing | cs.LG | We consider unsupervised crowdsourcing performance based on the model wherein
the responses of end-users are essentially rated according to how their
responses correlate with the majority of other responses to the same
subtasks/questions. In one setting, we consider an independent sequence of
identically distributed cr... | computer science |
40,458 | A Behavior-based Approach for Multi-agent Q-learning for Autonomous
Exploration | cs.RO | The use of mobile robots is being popular over the world mainly for
autonomous explorations in hazardous/ toxic or unknown environments. This
exploration will be more effective and efficient if the explorations in unknown
environment can be aided with the learning from past experiences. Currently
reinforcement learning... | computer science |
40,459 | A Variant of Azuma's Inequality for Martingales with Subgaussian Tails | cs.LG | We provide a variant of Azuma's concentration inequality for martingales, in
which the standard boundedness requirement is replaced by the milder
requirement of a subgaussian tail. | computer science |
40,460 | Issues,Challenges and Tools of Clustering Algorithms | cs.IR | Clustering is an unsupervised technique of Data Mining. It means grouping
similar objects together and separating the dissimilar ones. Each object in the
data set is assigned a class label in the clustering process using a distance
measure. This paper has captured the problems that are faced in real when
clustering alg... | computer science |
40,461 | Analysis of Heart Diseases Dataset using Neural Network Approach | cs.LG | One of the important techniques of Data mining is Classification. Many real
world problems in various fields such as business, science, industry and
medicine can be solved by using classification approach. Neural Networks have
emerged as an important tool for classification. The advantages of Neural
Networks helps for ... | computer science |
40,462 | A tail inequality for quadratic forms of subgaussian random vectors | math.PR | We prove an exponential probability tail inequality for positive semidefinite
quadratic forms in a subgaussian random vector. The bound is analogous to one
that holds when the vector has independent Gaussian entries. | computer science |
40,463 | Randomized Dimensionality Reduction for k-means Clustering | cs.DS | We study the topic of dimensionality reduction for $k$-means clustering.
Dimensionality reduction encompasses the union of two approaches: \emph{feature
selection} and \emph{feature extraction}. A feature selection based algorithm
for $k$-means clustering selects a small subset of the input features and then
applies $k... | computer science |
40,464 | Step size adaptation in first-order method for stochastic strongly
convex programming | math.OC | We propose a first-order method for stochastic strongly convex optimization
that attains $O(1/n)$ rate of convergence, analysis show that the proposed
method is simple, easily to implement, and in worst case, asymptotically four
times faster than its peers. We derive this method from several intuitive
observations that... | computer science |
40,465 | A critical evaluation of network and pathway based classifiers for
outcome prediction in breast cancer | cs.LG | Recently, several classifiers that combine primary tumor data, like gene
expression data, and secondary data sources, such as protein-protein
interaction networks, have been proposed for predicting outcome in breast
cancer. In these approaches, new composite features are typically constructed
by aggregating the express... | computer science |
40,466 | How to Evaluate Dimensionality Reduction? - Improving the Co-ranking
Matrix | cs.LG | The growing number of dimensionality reduction methods available for data
visualization has recently inspired the development of quality assessment
measures, in order to evaluate the resulting low-dimensional representation
independently from a methods' inherent criteria. Several (existing) quality
measures can be (re)... | computer science |
40,467 | Aspiration Learning in Coordination Games | cs.GT | We consider the problem of distributed convergence to efficient outcomes in
coordination games through dynamics based on aspiration learning. Under
aspiration learning, a player continues to play an action as long as the
rewards received exceed a specified aspiration level. Here, the aspiration
level is a fading memory... | computer science |
40,468 | Optimal discovery with probabilistic expert advice | math.OC | We consider an original problem that arises from the issue of security
analysis of a power system and that we name optimal discovery with
probabilistic expert advice. We address it with an algorithm based on the
optimistic paradigm and the Good-Turing missing mass estimator. We show that
this strategy uniformly attains... | computer science |
40,469 | Computing a Nonnegative Matrix Factorization -- Provably | cs.DS | In the Nonnegative Matrix Factorization (NMF) problem we are given an $n
\times m$ nonnegative matrix $M$ and an integer $r > 0$. Our goal is to express
$M$ as $A W$ where $A$ and $W$ are nonnegative matrices of size $n \times r$
and $r \times m$ respectively. In some applications, it makes sense to ask
instead for the... | computer science |
40,470 | Tight Bounds on Proper Equivalence Query Learning of DNF | cs.LG | We prove a new structural lemma for partial Boolean functions $f$, which we
call the seed lemma for DNF. Using the lemma, we give the first subexponential
algorithm for proper learning of DNF in Angluin's Equivalence Query (EQ) model.
The algorithm has time and query complexity $2^{(\tilde{O}{\sqrt{n}})}$, which
is opt... | computer science |
40,471 | Nonparametric Bayesian Estimation of Periodic Functions | cs.LG | Many real world problems exhibit patterns that have periodic behavior. For
example, in astrophysics, periodic variable stars play a pivotal role in
understanding our universe. An important step when analyzing data from such
processes is the problem of identifying the period: estimating the period of a
periodic function... | computer science |
40,472 | Analysis of Thompson Sampling for the multi-armed bandit problem | cs.LG | The multi-armed bandit problem is a popular model for studying
exploration/exploitation trade-off in sequential decision problems. Many
algorithms are now available for this well-studied problem. One of the earliest
algorithms, given by W. R. Thompson, dates back to 1933. This algorithm,
referred to as Thompson Samplin... | computer science |
40,473 | Pushing Your Point of View: Behavioral Measures of Manipulation in
Wikipedia | cs.SI | As a major source for information on virtually any topic, Wikipedia serves an
important role in public dissemination and consumption of knowledge. As a
result, it presents tremendous potential for people to promulgate their own
points of view; such efforts may be more subtle than typical vandalism. In this
paper, we in... | computer science |
40,474 | Generic Multiplicative Methods for Implementing Machine Learning
Algorithms on MapReduce | cs.DS | In this paper we introduce a generic model for multiplicative algorithms
which is suitable for the MapReduce parallel programming paradigm. We implement
three typical machine learning algorithms to demonstrate how similarity
comparison, gradient descent, power method and other classic learning
techniques fit this model... | computer science |
40,475 | Improved Bound for the Nystrom's Method and its Application to Kernel
Classification | cs.LG | We develop two approaches for analyzing the approximation error bound for the
Nystr\"{o}m method, one based on the concentration inequality of integral
operator, and one based on the compressive sensing theory. We show that the
approximation error, measured in the spectral norm, can be improved from
$O(N/\sqrt{m})$ to ... | computer science |
40,476 | A Collaborative Mechanism for Crowdsourcing Prediction Problems | cs.LG | Machine Learning competitions such as the Netflix Prize have proven
reasonably successful as a method of "crowdsourcing" prediction tasks. But
these competitions have a number of weaknesses, particularly in the incentive
structure they create for the participants. We propose a new approach, called a
Crowdsourced Learni... | computer science |
40,477 | Using Contextual Information as Virtual Items on Top-N Recommender
Systems | cs.LG | Traditionally, recommender systems for the Web deal with applications that
have two dimensions, users and items. Based on access logs that relate these
dimensions, a recommendation model can be built and used to identify a set of N
items that will be of interest to a certain user. In this paper we propose a
method to c... | computer science |
40,478 | The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian
Monte Carlo | stat.CO | Hamiltonian Monte Carlo (HMC) is a Markov chain Monte Carlo (MCMC) algorithm
that avoids the random walk behavior and sensitivity to correlated parameters
that plague many MCMC methods by taking a series of steps informed by
first-order gradient information. These features allow it to converge to
high-dimensional targe... | computer science |
40,479 | Learning with Submodular Functions: A Convex Optimization Perspective | cs.LG | Submodular functions are relevant to machine learning for at least two
reasons: (1) some problems may be expressed directly as the optimization of
submodular functions and (2) the lovasz extension of submodular functions
provides a useful set of regularization functions for supervised and
unsupervised learning. In this... | computer science |
40,480 | A Learning Framework for Self-Tuning Histograms | cs.DB | In this paper, we consider the problem of estimating self-tuning histograms
using query workloads. To this end, we propose a general learning theoretic
formulation. Specifically, we use query feedback from a workload as training
data to estimate a histogram with a small memory footprint that minimizes the
expected erro... | computer science |
40,481 | Scikit-learn: Machine Learning in Python | cs.LG | Scikit-learn is a Python module integrating a wide range of state-of-the-art
machine learning algorithms for medium-scale supervised and unsupervised
problems. This package focuses on bringing machine learning to non-specialists
using a general-purpose high-level language. Emphasis is put on ease of use,
performance, d... | computer science |
40,482 | Joint Approximation of Information and Distributed Link-Scheduling
Decisions in Wireless Networks | cs.LG | For a large multi-hop wireless network, nodes are preferable to make
distributed and localized link-scheduling decisions with only interactions
among a small number of neighbors. However, for a slowly decaying channel and
densely populated interferers, a small size neighborhood often results in
nontrivial link outages ... | computer science |
40,483 | Combining Heterogeneous Classifiers for Relational Databases | cs.LG | Most enterprise data is distributed in multiple relational databases with
expert-designed schema. Using traditional single-table machine learning
techniques over such data not only incur a computational penalty for converting
to a 'flat' form (mega-join), even the human-specified semantic information
present in the rel... | computer science |
40,484 | Adaptive Shortest-Path Routing under Unknown and Stochastically Varying
Link States | cs.NI | We consider the adaptive shortest-path routing problem in wireless networks
under unknown and stochastically varying link states. In this problem, we aim
to optimize the quality of communication between a source and a destination
through adaptive path selection. Due to the randomness and uncertainties in the
network dy... | computer science |
40,485 | A Bayesian Approach to Discovering Truth from Conflicting Sources for
Data Integration | cs.DB | In practical data integration systems, it is common for the data sources
being integrated to provide conflicting information about the same entity.
Consequently, a major challenge for data integration is to derive the most
complete and accurate integrated records from diverse and sometimes conflicting
sources. We term ... | computer science |
40,486 | Graph partitioning advance clustering technique | cs.LG | Clustering is a common technique for statistical data analysis, Clustering is
the process of grouping the data into classes or clusters so that objects
within a cluster have high similarity in comparison to one another, but are
very dissimilar to objects in other clusters. Dissimilarities are assessed
based on the attr... | computer science |
40,487 | Mining Education Data to Predict Student's Retention: A comparative
Study | cs.LG | The main objective of higher education is to provide quality education to
students. One way to achieve highest level of quality in higher education
system is by discovering knowledge for prediction regarding enrolment of
students in a course. This paper presents a data mining project to generate
predictive models for s... | computer science |
40,488 | Distributed Cooperative Q-learning for Power Allocation in Cognitive
Femtocell Networks | cs.LG | In this paper, we propose a distributed reinforcement learning (RL) technique
called distributed power control using Q-learning (DPC-Q) to manage the
interference caused by the femtocells on macro-users in the downlink. The DPC-Q
leverages Q-Learning to identify the sub-optimal pattern of power allocation,
which strive... | computer science |
40,489 | Parallel Matrix Factorization for Binary Response | cs.LG | Predicting user affinity to items is an important problem in applications
like content optimization, computational advertising, and many more. While
bilinear random effect models (matrix factorization) provide state-of-the-art
performance when minimizing RMSE through a Gaussian response model on explicit
ratings data, ... | computer science |
40,490 | A Bayesian Model Committee Approach to Forecasting Global Solar
Radiation | stat.AP | This paper proposes to use a rather new modelling approach in the realm of
solar radiation forecasting. In this work, two forecasting models:
Autoregressive Moving Average (ARMA) and Neural Network (NN) models are
combined to form a model committee. The Bayesian inference is used to affect a
probability to each model i... | computer science |
40,491 | Near-Optimal Algorithms for Online Matrix Prediction | cs.LG | In several online prediction problems of recent interest the comparison class
is composed of matrices with bounded entries. For example, in the online
max-cut problem, the comparison class is matrices which represent cuts of a
given graph and in online gambling the comparison class is matrices which
represent permutati... | computer science |
40,492 | A New Approach to Speeding Up Topic Modeling | cs.LG | Latent Dirichlet allocation (LDA) is a widely-used probabilistic topic
modeling paradigm, and recently finds many applications in computer vision and
computational biology. In this paper, we propose a fast and accurate batch
algorithm, active belief propagation (ABP), for training LDA. Usually batch LDA
algorithms requ... | computer science |
40,493 | Learning Fuzzy β-Certain and β-Possible rules from
incomplete quantitative data by rough sets | cs.DS | The rough-set theory proposed by Pawlak, has been widely used in dealing with
data classification problems. The original rough-set model is, however, quite
sensitive to noisy data. Tzung thus proposed deals with the problem of
producing a set of fuzzy certain and fuzzy possible rules from quantitative
data with a prede... | computer science |
40,494 | Minimal model of associative learning for cross-situational lexicon
acquisition | cs.LG | An explanation for the acquisition of word-object mappings is the associative
learning in a cross-situational scenario. Here we present analytical results of
the performance of a simple associative learning algorithm for acquiring a
one-to-one mapping between $N$ objects and $N$ words based solely on the
co-occurrence ... | computer science |
40,495 | A technical study and analysis on fuzzy similarity based models for text
classification | cs.IR | In this new and current era of technology, advancements and techniques,
efficient and effective text document classification is becoming a challenging
and highly required area to capably categorize text documents into mutually
exclusive categories. Fuzzy similarity provides a way to find the similarity of
features amon... | computer science |
40,496 | A Fuzzy Similarity Based Concept Mining Model for Text Classification | cs.IR | Text Classification is a challenging and a red hot field in the current
scenario and has great importance in text categorization applications. A lot of
research work has been done in this field but there is a need to categorize a
collection of text documents into mutually exclusive categories by extracting
the concepts... | computer science |
40,497 | Plug-in martingales for testing exchangeability on-line | cs.LG | A standard assumption in machine learning is the exchangeability of data,
which is equivalent to assuming that the examples are generated from the same
probability distribution independently. This paper is devoted to testing the
assumption of exchangeability on-line: the examples arrive one by one, and
after receiving ... | computer science |
40,498 | Distributed Learning, Communication Complexity and Privacy | cs.LG | We consider the problem of PAC-learning from distributed data and analyze
fundamental communication complexity questions involved. We provide general
upper and lower bounds on the amount of communication needed to learn well,
showing that in addition to VC-dimension and covering number, quantities such
as the teaching-... | computer science |
40,499 | Learning to Predict the Wisdom of Crowds | cs.SI | The problem of "approximating the crowd" is that of estimating the crowd's
majority opinion by querying only a subset of it. Algorithms that approximate
the crowd can intelligently stretch a limited budget for a crowdsourcing task.
We present an algorithm, "CrowdSense," that works in an online fashion to
dynamically sa... | computer science |
40,500 | Learning From An Optimization Viewpoint | cs.LG | In this dissertation we study statistical and online learning problems from
an optimization viewpoint.The dissertation is divided into two parts :
I. We first consider the question of learnability for statistical learning
problems in the general learning setting. The question of learnability is well
studied and fully... | computer science |
40,501 | Designing generalisation evaluation function through human-machine
dialogue | cs.HC | Automated generalisation has known important improvements these last few
years. However, an issue that still deserves more study concerns the automatic
evaluation of generalised data. Indeed, many automated generalisation systems
require the utilisation of an evaluation function to automatically assess
generalisation o... | computer science |
40,502 | Quantitative Concept Analysis | cs.LG | Formal Concept Analysis (FCA) begins from a context, given as a binary
relation between some objects and some attributes, and derives a lattice of
concepts, where each concept is given as a set of objects and a set of
attributes, such that the first set consists of all objects that satisfy all
attributes in the second,... | computer science |
40,503 | Geometry of Online Packing Linear Programs | cs.DS | We consider packing LP's with $m$ rows where all constraint coefficients are
normalized to be in the unit interval. The n columns arrive in random order and
the goal is to set the corresponding decision variables irrevocably when they
arrive so as to obtain a feasible solution maximizing the expected reward.
Previous (... | computer science |
40,504 | Distributed GraphLab: A Framework for Machine Learning in the Cloud | cs.DB | While high-level data parallel frameworks, like MapReduce, simplify the
design and implementation of large-scale data processing systems, they do not
naturally or efficiently support many important data mining and machine
learning algorithms and can lead to inefficient learning systems. To help fill
this critical void,... | computer science |
40,505 | Feature Selection for Generator Excitation Neurocontroller Development
Using Filter Technique | cs.SY | Essentially, motive behind using control system is to generate suitable
control signal for yielding desired response of a physical process. Control of
synchronous generator has always remained very critical in power system
operation and control. For certain well known reasons power generators are
normally operated well... | computer science |
40,506 | CELL: Connecting Everyday Life in an archipeLago | cs.HC | We explore the design of a seamless broadcast communication system that
brings together the distributed community of remote secondary education
schools. In contrast to higher education, primary and secondary education
establishments should remain distributed, in order to maintain a balance of
urban and rural life in th... | computer science |
40,507 | Residual Belief Propagation for Topic Modeling | cs.LG | Fast convergence speed is a desired property for training latent Dirichlet
allocation (LDA), especially in online and parallel topic modeling for massive
data sets. This paper presents a novel residual belief propagation (RBP)
algorithm to accelerate the convergence speed for training LDA. The proposed
RBP uses an info... | computer science |
40,508 | Detection of Deviations in Mobile Applications Network Behavior | cs.CR | In this paper a novel system for detecting meaningful deviations in a mobile
application's network behavior is proposed. The main goal of the proposed
system is to protect mobile device users and cellular infrastructure companies
from malicious applications. The new system is capable of: (1) identifying
malicious attac... | computer science |
40,509 | A Random Walk Based Model Incorporating Social Information for
Recommendations | cs.IR | Collaborative filtering (CF) is one of the most popular approaches to build a
recommendation system. In this paper, we propose a hybrid collaborative
filtering model based on a Makovian random walk to address the data sparsity
and cold start problems in recommendation systems. More precisely, we construct
a directed gr... | computer science |
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