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40,510 | Self-Organizing Time Map: An Abstraction of Temporal Multivariate
Patterns | cs.LG | This paper adopts and adapts Kohonen's standard Self-Organizing Map (SOM) for
exploratory temporal structure analysis. The Self-Organizing Time Map (SOTM)
implements SOM-type learning to one-dimensional arrays for individual time
units, preserves the orientation with short-term memory and arranges the arrays
in an asce... | computer science |
40,511 | Scaling Multiple-Source Entity Resolution using Statistically Efficient
Transfer Learning | cs.DB | We consider a serious, previously-unexplored challenge facing almost all
approaches to scaling up entity resolution (ER) to multiple data sources: the
prohibitive cost of labeling training data for supervised learning of
similarity scores for each pair of sources. While there exists a rich
literature describing almost ... | computer science |
40,512 | Analysis of a Statistical Hypothesis Based Learning Mechanism for Faster
crawling | cs.LG | The growth of world-wide-web (WWW) spreads its wings from an intangible
quantities of web-pages to a gigantic hub of web information which gradually
increases the complexity of crawling process in a search engine. A search
engine handles a lot of queries from various parts of this world, and the
answers of it solely de... | computer science |
40,513 | Metric distances derived from cosine similarity and Pearson and Spearman
correlations | stat.ME | We investigate two classes of transformations of cosine similarity and
Pearson and Spearman correlations into metric distances, utilising the simple
tool of metric-preserving functions. The first class puts anti-correlated
objects maximally far apart. Previously known transforms fall within this
class. The second class... | computer science |
40,514 | A Learning Theoretic Approach to Energy Harvesting Communication System
Optimization | cs.LG | A point-to-point wireless communication system in which the transmitter is
equipped with an energy harvesting device and a rechargeable battery, is
studied. Both the energy and the data arrivals at the transmitter are modeled
as Markov processes. Delay-limited communication is considered assuming that
the underlying ch... | computer science |
40,515 | Identification of Probabilities of Languages | cs.LG | We consider the problem of inferring the probability distribution associated
with a language, given data consisting of an infinite sequence of elements of
the languge. We do this under two assumptions on the algorithms concerned: (i)
like a real-life algorothm it has round-off errors, and (ii) it has no
round-off error... | computer science |
40,516 | Fixed-rank matrix factorizations and Riemannian low-rank optimization | cs.LG | Motivated by the problem of learning a linear regression model whose
parameter is a large fixed-rank non-symmetric matrix, we consider the
optimization of a smooth cost function defined on the set of fixed-rank
matrices. We adopt the geometric framework of optimization on Riemannian
quotient manifolds. We study the und... | computer science |
40,517 | Design of Spectrum Sensing Policy for Multi-user Multi-band Cognitive
Radio Network | cs.LG | Finding an optimal sensing policy for a particular access policy and sensing
scheme is a laborious combinatorial problem that requires the system model
parameters to be known. In practise the parameters or the model itself may not
be completely known making reinforcement learning methods appealing. In this
paper a non-... | computer science |
40,518 | Securing Your Transactions: Detecting Anomalous Patterns In XML
Documents | cs.CR | XML transactions are used in many information systems to store data and
interact with other systems. Abnormal transactions, the result of either an
on-going cyber attack or the actions of a benign user, can potentially harm the
interacting systems and therefore they are regarded as a threat. In this paper
we address th... | computer science |
40,519 | Active Learning for Crowd-Sourced Databases | cs.LG | Crowd-sourcing has become a popular means of acquiring labeled data for a
wide variety of tasks where humans are more accurate than computers, e.g.,
labeling images, matching objects, or analyzing sentiment. However, relying
solely on the crowd is often impractical even for data sets with thousands of
items, due to tim... | computer science |
40,520 | On the Sensitivity of Shape Fitting Problems | cs.CG | In this article, we study shape fitting problems, $\epsilon$-coresets, and
total sensitivity. We focus on the $(j,k)$-projective clustering problems,
including $k$-median/$k$-means, $k$-line clustering, $j$-subspace
approximation, and the integer $(j,k)$-projective clustering problem. We derive
upper bounds of total se... | computer science |
40,521 | Locality-Sensitive Hashing with Margin Based Feature Selection | cs.LG | We propose a learning method with feature selection for Locality-Sensitive
Hashing. Locality-Sensitive Hashing converts feature vectors into bit arrays.
These bit arrays can be used to perform similarity searches and personal
authentication. The proposed method uses bit arrays longer than those used in
the end for simi... | computer science |
40,522 | Learning Robust Low-Rank Representations | cs.LG | In this paper we present a comprehensive framework for learning robust
low-rank representations by combining and extending recent ideas for learning
fast sparse coding regressors with structured non-convex optimization
techniques. This approach connects robust principal component analysis (RPCA)
with dictionary learnin... | computer science |
40,523 | Gene selection with guided regularized random forest | cs.LG | The regularized random forest (RRF) was recently proposed for feature
selection by building only one ensemble. In RRF the features are evaluated on a
part of the training data at each tree node. We derive an upper bound for the
number of distinct Gini information gain values in a node, and show that many
features can s... | computer science |
40,524 | CloudSVM : Training an SVM Classifier in Cloud Computing Systems | cs.LG | In conventional method, distributed support vector machines (SVM) algorithms
are trained over pre-configured intranet/internet environments to find out an
optimal classifier. These methods are very complicated and costly for large
datasets. Hence, we propose a method that is referred as the Cloud SVM training
mechanism... | computer science |
40,525 | An Efficient Algorithm for Upper Bound on the Partition Function of
Nucleic Acids | cs.LG | It has been shown that minimum free energy structure for RNAs and RNA-RNA
interaction is often incorrect due to inaccuracies in the energy parameters and
inherent limitations of the energy model. In contrast, ensemble based
quantities such as melting temperature and equilibrium concentrations can be
more reliably predi... | computer science |
40,526 | Symmetric Collaborative Filtering Using the Noisy Sensor Model | cs.IR | Collaborative filtering is the process of making recommendations regarding
the potential preference of a user, for example shopping on the Internet, based
on the preference ratings of the user and a number of other users for various
items. This paper considers collaborative filtering based on
explicitmulti-valued ratin... | computer science |
40,527 | A comparison of SVM and RVM for Document Classification | cs.IR | Document classification is a task of assigning a new unclassified document to
one of the predefined set of classes. The content based document classification
uses the content of the document with some weighting criteria to assign it to
one of the predefined classes. It is a major task in library science,
electronic doc... | computer science |
40,528 | The Diagonalized Newton Algorithm for Nonnegative Matrix Factorization | cs.NA | Non-negative matrix factorization (NMF) has become a popular machine learning
approach to many problems in text mining, speech and image processing,
bio-informatics and seismic data analysis to name a few. In NMF, a matrix of
non-negative data is approximated by the low-rank product of two matrices with
non-negative en... | computer science |
40,529 | Block Coordinate Descent for Sparse NMF | cs.LG | Nonnegative matrix factorization (NMF) has become a ubiquitous tool for data
analysis. An important variant is the sparse NMF problem which arises when we
explicitly require the learnt features to be sparse. A natural measure of
sparsity is the L$_0$ norm, however its optimization is NP-hard. Mixed norms,
such as L$_1$... | computer science |
40,530 | Revisiting Natural Gradient for Deep Networks | cs.LG | We evaluate natural gradient, an algorithm originally proposed in Amari
(1997), for learning deep models. The contributions of this paper are as
follows. We show the connection between natural gradient and three other
recently proposed methods for training deep models: Hessian-Free (Martens,
2010), Krylov Subspace Desc... | computer science |
40,531 | Empirical Analysis of Predictive Algorithms for Collaborative Filtering | cs.IR | Collaborative filtering or recommender systems use a database about user
preferences to predict additional topics or products a new user might like. In
this paper we describe several algorithms designed for this task, including
techniques based on correlation coefficients, vector-based similarity
calculations, and stat... | computer science |
40,532 | Generalization Bounds for Domain Adaptation | cs.LG | In this paper, we provide a new framework to obtain the generalization bounds
of the learning process for domain adaptation, and then apply the derived
bounds to analyze the asymptotical convergence of the learning process. Without
loss of generality, we consider two kinds of representative domain adaptation:
one is wi... | computer science |
40,533 | Image Retrieval based on Bag-of-Words model | cs.IR | This article gives a survey for bag-of-words (BoW) or bag-of-features model
in image retrieval system. In recent years, large-scale image retrieval shows
significant potential in both industry applications and research problems. As
local descriptors like SIFT demonstrate great discriminative power in solving
vision pro... | computer science |
40,534 | North Atlantic Right Whale Contact Call Detection | cs.LG | The North Atlantic right whale (Eubalaena glacialis) is an endangered
species. These whales continuously suffer from deadly vessel impacts alongside
the eastern coast of North America. There have been countless efforts to save
the remaining 350 - 400 of them. One of the most prominent works is done by
Marinexplore and ... | computer science |
40,535 | Dynamic Ad Allocation: Bandits with Budgets | cs.LG | We consider an application of multi-armed bandits to internet advertising
(specifically, to dynamic ad allocation in the pay-per-click model, with
uncertainty on the click probabilities). We focus on an important practical
issue that advertisers are constrained in how much money they can spend on
their ad campaigns. Th... | computer science |
40,536 | KERT: Automatic Extraction and Ranking of Topical Keyphrases from
Content-Representative Document Titles | cs.LG | We introduce KERT (Keyphrase Extraction and Ranking by Topic), a framework
for topical keyphrase generation and ranking. By shifting from the
unigram-centric traditional methods of unsupervised keyphrase extraction to a
phrase-centric approach, we are able to directly compare and rank phrases of
different lengths. We c... | computer science |
40,537 | Identifying Pairs in Simulated Bio-Medical Time-Series | cs.LG | The paper presents a time-series-based classification approach to identify
similarities in pairs of simulated human-generated patterns. An example for a
pattern is a time-series representing a heart rate during a specific
time-range, wherein the time-series is a sequence of data points that represent
the changes in the... | computer science |
40,538 | Highly Scalable, Parallel and Distributed AdaBoost Algorithm using Light
Weight Threads and Web Services on a Network of Multi-Core Machines | cs.DC | AdaBoost is an important algorithm in machine learning and is being widely
used in object detection. AdaBoost works by iteratively selecting the best
amongst weak classifiers, and then combines several weak classifiers to obtain
a strong classifier. Even though AdaBoost has proven to be very effective, its
learning exe... | computer science |
40,539 | Predicting Risk-of-Readmission for Congestive Heart Failure Patients: A
Multi-Layer Approach | cs.LG | Mitigating risk-of-readmission of Congestive Heart Failure (CHF) patients
within 30 days of discharge is important because such readmissions are not only
expensive but also critical indicator of provider care and quality of
treatment. Accurately predicting the risk-of-readmission may allow hospitals to
identify high-ri... | computer science |
40,540 | A Novel Approach for Single Gene Selection Using Clustering and
Dimensionality Reduction | cs.CE | We extend the standard rough set-based approach to deal with huge amounts of
numeric attributes versus small amount of available objects. Here, a novel
approach of clustering along with dimensionality reduction; Hybrid Fuzzy C
Means-Quick Reduct (FCMQR) algorithm is proposed for single gene selection.
Gene selection is... | computer science |
40,541 | Large Margin Low Rank Tensor Analysis | cs.LG | Other than vector representations, the direct objects of human cognition are
generally high-order tensors, such as 2D images and 3D textures. From this
fact, two interesting questions naturally arise: How does the human brain
represent these tensor perceptions in a "manifold" way, and how can they be
recognized on the ... | computer science |
40,542 | R3MC: A Riemannian three-factor algorithm for low-rank matrix completion | math.OC | We exploit the versatile framework of Riemannian optimization on quotient
manifolds to develop R3MC, a nonlinear conjugate-gradient method for low-rank
matrix completion. The underlying search space of fixed-rank matrices is
endowed with a novel Riemannian metric that is tailored to the least-squares
cost. Numerical co... | computer science |
40,543 | Approximation Algorithms for Bayesian Multi-Armed Bandit Problems | cs.DS | In this paper, we consider several finite-horizon Bayesian multi-armed bandit
problems with side constraints which are computationally intractable (NP-Hard)
and for which no optimal (or near optimal) algorithms are known to exist with
sub-exponential running time. All of these problems violate the standard
exchange pro... | computer science |
40,544 | Online Alternating Direction Method (longer version) | cs.LG | Online optimization has emerged as powerful tool in large scale optimization.
In this pa- per, we introduce efficient online optimization algorithms based on
the alternating direction method (ADM), which can solve online convex
optimization under linear constraints where the objective could be non-smooth.
We introduce ... | computer science |
40,545 | Cluster coloring of the Self-Organizing Map: An information
visualization perspective | cs.LG | This paper takes an information visualization perspective to visual
representations in the general SOM paradigm. This involves viewing SOM-based
visualizations through the eyes of Bertin's and Tufte's theories on data
graphics. The regular grid shape of the Self-Organizing Map (SOM), while being
a virtue for linking vi... | computer science |
40,546 | Parallel Coordinate Descent Newton Method for Efficient
$\ell_1$-Regularized Minimization | cs.LG | The recent years have witnessed advances in parallel algorithms for large
scale optimization problems. Notwithstanding demonstrated success, existing
algorithms that parallelize over features are usually limited by divergence
issues under high parallelism or require data preprocessing to alleviate these
problems. In th... | computer science |
40,547 | A Fuzzy Based Approach to Text Mining and Document Clustering | cs.LG | Fuzzy logic deals with degrees of truth. In this paper, we have shown how to
apply fuzzy logic in text mining in order to perform document clustering. We
took an example of document clustering where the documents had to be clustered
into two categories. The method involved cleaning up the text and stemming of
words. Th... | computer science |
40,548 | From-Below Approximations in Boolean Matrix Factorization: Geometry and
New Algorithm | cs.NA | We present new results on Boolean matrix factorization and a new algorithm
based on these results. The results emphasize the significance of
factorizations that provide from-below approximations of the input matrix.
While the previously proposed algorithms do not consider the possibly different
significance of differen... | computer science |
40,549 | An efficient reduction of ranking to classification | cs.LG | This paper describes an efficient reduction of the learning problem of
ranking to binary classification. The reduction guarantees an average pairwise
misranking regret of at most that of the binary classifier regret, improving a
recent result of Balcan et al which only guarantees a factor of 2. Moreover,
our reduction ... | computer science |
40,550 | Bias-Variance Techniques for Monte Carlo Optimization: Cross-validation
for the CE Method | cs.NA | In this paper, we examine the CE method in the broad context of Monte Carlo
Optimization (MCO) and Parametric Learning (PL), a type of machine learning. A
well-known overarching principle used to improve the performance of many PL
algorithms is the bias-variance tradeoff. This tradeoff has been used to
improve PL algor... | computer science |
40,551 | Blind Cognitive MAC Protocols | cs.NI | We consider the design of cognitive Medium Access Control (MAC) protocols
enabling an unlicensed (secondary) transmitter-receiver pair to communicate
over the idle periods of a set of licensed channels, i.e., the primary network.
The objective is to maximize data throughput while maintaining the
synchronization between... | computer science |
40,552 | A Simple Linear Ranking Algorithm Using Query Dependent Intercept
Variables | cs.IR | The LETOR website contains three information retrieval datasets used as a
benchmark for testing machine learning ideas for ranking. Algorithms
participating in the challenge are required to assign score values to search
results for a collection of queries, and are measured using standard IR ranking
measures (NDCG, prec... | computer science |
40,553 | Median topographic maps for biomedical data sets | cs.LG | Median clustering extends popular neural data analysis methods such as the
self-organizing map or neural gas to general data structures given by a
dissimilarity matrix only. This offers flexible and robust global data
inspection methods which are particularly suited for a variety of data as
occurs in biomedical domains... | computer science |
40,554 | Sailing the Information Ocean with Awareness of Currents: Discovery and
Application of Source Dependence | cs.DB | The Web has enabled the availability of a huge amount of useful information,
but has also eased the ability to spread false information and rumors across
multiple sources, making it hard to distinguish between what is true and what
is not. Recent examples include the premature Steve Jobs obituary, the second
bankruptcy... | computer science |
40,555 | Distribution-Specific Agnostic Boosting | cs.LG | We consider the problem of boosting the accuracy of weak learning algorithms
in the agnostic learning framework of Haussler (1992) and Kearns et al. (1992).
Known algorithms for this problem (Ben-David et al., 2001; Gavinsky, 2002;
Kalai et al., 2008) follow the same strategy as boosting algorithms in the PAC
model: th... | computer science |
40,556 | Bounding the Sensitivity of Polynomial Threshold Functions | cs.CC | We give the first non-trivial upper bounds on the average sensitivity and
noise sensitivity of polynomial threshold functions. More specifically, for a
Boolean function f on n variables equal to the sign of a real, multivariate
polynomial of total degree d we prove
1) The average sensitivity of f is at most O(n^{1-1/... | computer science |
40,557 | "Memory foam" approach to unsupervised learning | nlin.AO | We propose an alternative approach to construct an artificial learning
system, which naturally learns in an unsupervised manner. Its mathematical
prototype is a dynamical system, which automatically shapes its vector field in
response to the input signal. The vector field converges to a gradient of a
multi-dimensional ... | computer science |
40,558 | Data Stability in Clustering: A Closer Look | cs.LG | We consider the model introduced by Bilu and Linial (2010), who study
problems for which the optimal clustering does not change when distances are
perturbed. They show that even when a problem is NP-hard, it is sometimes
possible to obtain efficient algorithms for instances resilient to certain
multiplicative perturbat... | computer science |
40,559 | Private Data Release via Learning Thresholds | cs.CC | This work considers computationally efficient privacy-preserving data
release. We study the task of analyzing a database containing sensitive
information about individual participants. Given a set of statistical queries
on the data, we want to release approximate answers to the queries while also
guaranteeing different... | computer science |
40,560 | Optimal Adaptive Learning in Uncontrolled Restless Bandit Problems | math.OC | In this paper we consider the problem of learning the optimal policy for
uncontrolled restless bandit problems. In an uncontrolled restless bandit
problem, there is a finite set of arms, each of which when pulled yields a
positive reward. There is a player who sequentially selects one of the arms at
each time step. The... | computer science |
40,561 | Performance and Convergence of Multi-user Online Learning | cs.MA | We study the problem of allocating multiple users to a set of wireless
channels in a decentralized manner when the channel quali- ties are
time-varying and unknown to the users, and accessing the same channel by
multiple users leads to reduced quality due to interference. In such a setting
the users not only need to le... | computer science |
40,562 | Using Incomplete Information for Complete Weight Annotation of Road
Networks -- Extended Version | cs.LG | We are witnessing increasing interests in the effective use of road networks.
For example, to enable effective vehicle routing, weighted-graph models of
transportation networks are used, where the weight of an edge captures some
cost associated with traversing the edge, e.g., greenhouse gas (GHG) emissions
or travel ti... | computer science |
40,563 | MonoStream: A Minimal-Hardware High Accuracy Device-free WLAN
Localization System | cs.NI | Device-free (DF) localization is an emerging technology that allows the
detection and tracking of entities that do not carry any devices nor
participate actively in the localization process. Typically, DF systems require
a large number of transmitters and receivers to achieve acceptable accuracy,
which is not available... | computer science |
40,564 | Theoretical Issues for Global Cumulative Treatment Analysis (GCTA) | stat.AP | Adaptive trials are now mainstream science. Recently, researchers have taken
the adaptive trial concept to its natural conclusion, proposing what we call
"Global Cumulative Treatment Analysis" (GCTA). Similar to the adaptive trial,
decision making and data collection and analysis in the GCTA are continuous and
integrat... | computer science |
40,565 | OFF-Set: One-pass Factorization of Feature Sets for Online
Recommendation in Persistent Cold Start Settings | cs.LG | One of the most challenging recommendation tasks is recommending to a new,
previously unseen user. This is known as the 'user cold start' problem.
Assuming certain features or attributes of users are known, one approach for
handling new users is to initially model them based on their features.
Motivated by an ad targ... | computer science |
40,566 | Normalized Google Distance of Multisets with Applications | cs.IR | Normalized Google distance (NGD) is a relative semantic distance based on the
World Wide Web (or any other large electronic database, for instance Wikipedia)
and a search engine that returns aggregate page counts. The earlier NGD between
pairs of search terms (including phrases) is not sufficient for all
applications. ... | computer science |
40,567 | Fast Stochastic Alternating Direction Method of Multipliers | cs.LG | In this paper, we propose a new stochastic alternating direction method of
multipliers (ADMM) algorithm, which incrementally approximates the full
gradient in the linearized ADMM formulation. Besides having a low per-iteration
complexity as existing stochastic ADMM algorithms, the proposed algorithm
improves the conver... | computer science |
40,568 | Nested Nonnegative Cone Analysis | stat.ME | Motivated by the analysis of nonnegative data objects, a novel Nested
Nonnegative Cone Analysis (NNCA) approach is proposed to overcome some
drawbacks of existing methods. The application of traditional PCA/SVD method to
nonnegative data often cause the approximation matrix leave the nonnegative
cone, which leads to no... | computer science |
40,569 | Decentralized Online Big Data Classification - a Bandit Framework | cs.LG | Distributed, online data mining systems have emerged as a result of
applications requiring analysis of large amounts of correlated and
high-dimensional data produced by multiple distributed data sources. We propose
a distributed online data classification framework where data is gathered by
distributed data sources and... | computer science |
40,570 | Considering users' behaviours in improving the responses of an
information base | cs.LG | In this paper, our aim is to propose a model that helps in the efficient use
of an information system by users, within the organization represented by the
IS, in order to resolve their decisional problems. In other words we want to
aid the user within an organization in obtaining the information that
corresponds to his... | computer science |
40,571 | Using state space differential geometry for nonlinear blind source
separation | cs.LG | Given a time series of multicomponent measurements of an evolving stimulus,
nonlinear blind source separation (BSS) seeks to find a "source" time series,
comprised of statistically independent combinations of the measured components.
In this paper, we seek a source time series with local velocity cross
correlations tha... | computer science |
40,572 | Statistical Mechanics of On-line Learning when a Moving Teacher Goes
around an Unlearnable True Teacher | cs.LG | In the framework of on-line learning, a learning machine might move around a
teacher due to the differences in structures or output functions between the
teacher and the learning machine. In this paper we analyze the generalization
performance of a new student supervised by a moving machine. A model composed
of a fixed... | computer science |
40,573 | Privacy Preserving ID3 over Horizontally, Vertically and Grid
Partitioned Data | cs.DB | We consider privacy preserving decision tree induction via ID3 in the case
where the training data is horizontally or vertically distributed. Furthermore,
we consider the same problem in the case where the data is both horizontally
and vertically distributed, a situation we refer to as grid partitioned data.
We give an... | computer science |
40,574 | Approximation Algorithms for Bregman Co-clustering and Tensor Clustering | cs.DS | In the past few years powerful generalizations to the Euclidean k-means
problem have been made, such as Bregman clustering [7], co-clustering (i.e.,
simultaneous clustering of rows and columns of an input matrix) [9,18], and
tensor clustering [8,34]. Like k-means, these more general problems also suffer
from the NP-har... | computer science |
40,575 | Decision trees are PAC-learnable from most product distributions: a
smoothed analysis | cs.LG | We consider the problem of PAC-learning decision trees, i.e., learning a
decision tree over the n-dimensional hypercube from independent random labeled
examples. Despite significant effort, no polynomial-time algorithm is known for
learning polynomial-sized decision trees (even trees of any super-constant
size), even w... | computer science |
40,576 | Uncovering protein interaction in abstracts and text using a novel
linear model and word proximity networks | cs.IR | We participated in three of the protein-protein interaction subtasks of the
Second BioCreative Challenge: classification of abstracts relevant for
protein-protein interaction (IAS), discovery of protein pairs (IPS) and text
passages characterizing protein interaction (ISS) in full text documents. We
approached the abst... | computer science |
40,577 | Decomposition Principles and Online Learning in Cross-Layer Optimization
for Delay-Sensitive Applications | cs.MM | In this paper, we propose a general cross-layer optimization framework in
which we explicitly consider both the heterogeneous and dynamically changing
characteristics of delay-sensitive applications and the underlying time-varying
network conditions. We consider both the independently decodable data units
(DUs, e.g. pa... | computer science |
40,578 | Comparison of Binary Classification Based on Signed Distance Functions
with Support Vector Machines | cs.LG | We investigate the performance of a simple signed distance function (SDF)
based method by direct comparison with standard SVM packages, as well as
K-nearest neighbor and RBFN methods. We present experimental results comparing
the SDF approach with other classifiers on both synthetic geometric problems
and five benchmar... | computer science |
40,579 | Quantum Predictive Learning and Communication Complexity with Single
Input | cs.LG | We define a new model of quantum learning that we call Predictive Quantum
(PQ). This is a quantum analogue of PAC, where during the testing phase the
student is only required to answer a polynomial number of testing queries.
We demonstrate a relational concept class that is efficiently learnable in
PQ, while in any "... | computer science |
40,580 | A New Local Distance-Based Outlier Detection Approach for Scattered
Real-World Data | cs.LG | Detecting outliers which are grossly different from or inconsistent with the
remaining dataset is a major challenge in real-world KDD applications. Existing
outlier detection methods are ineffective on scattered real-world datasets due
to implicit data patterns and parameter setting issues. We define a novel
"Local Dis... | computer science |
40,581 | Optimal Policies Search for Sensor Management | cs.LG | This paper introduces a new approach to solve sensor management problems.
Classically sensor management problems can be well formalized as
Partially-Observed Markov Decision Processes (POMPD). The original approach
developped here consists in deriving the optimal parameterized policy based on
a stochastic gradient esti... | computer science |
40,582 | Graph polynomials and approximation of partition functions with Loopy
Belief Propagation | cs.DM | The Bethe approximation, or loopy belief propagation algorithm is a
successful method for approximating partition functions of probabilistic models
associated with a graph. Chertkov and Chernyak derived an interesting formula
called Loop Series Expansion, which is an expansion of the partition function.
The main term o... | computer science |
40,583 | Bayesian Forecasting of WWW Traffic on the Time Varying Poisson Model | cs.NI | Traffic forecasting from past observed traffic data with small calculation
complexity is one of important problems for planning of servers and networks.
Focusing on World Wide Web (WWW) traffic as fundamental investigation, this
paper would deal with Bayesian forecasting of network traffic on the time
varying Poisson m... | computer science |
40,584 | Rough Set Model for Discovering Hybrid Association Rules | cs.DB | In this paper, the mining of hybrid association rules with rough set approach
is investigated as the algorithm RSHAR.The RSHAR algorithm is constituted of
two steps mainly. At first, to join the participant tables into a general table
to generate the rules which is expressing the relationship between two or more
domain... | computer science |
40,585 | Learning with Spectral Kernels and Heavy-Tailed Data | cs.LG | Two ubiquitous aspects of large-scale data analysis are that the data often
have heavy-tailed properties and that diffusion-based or spectral-based methods
are often used to identify and extract structure of interest. Perhaps
surprisingly, popular distribution-independent methods such as those based on
the VC dimension... | computer science |
40,586 | Statistical Analysis of Privacy and Anonymity Guarantees in Randomized
Security Protocol Implementations | cs.CR | Security protocols often use randomization to achieve probabilistic
non-determinism. This non-determinism, in turn, is used in obfuscating the
dependence of observable values on secret data. Since the correctness of
security protocols is very important, formal analysis of security protocols has
been widely studied in l... | computer science |
40,587 | Online Reinforcement Learning for Dynamic Multimedia Systems | cs.LG | In our previous work, we proposed a systematic cross-layer framework for
dynamic multimedia systems, which allows each layer to make autonomous and
foresighted decisions that maximize the system's long-term performance, while
meeting the application's real-time delay constraints. The proposed solution
solved the cross-... | computer science |
40,588 | Learning Gaussian Mixtures with Arbitrary Separation | cs.LG | In this paper we present a method for learning the parameters of a mixture of
$k$ identical spherical Gaussians in $n$-dimensional space with an arbitrarily
small separation between the components. Our algorithm is polynomial in all
parameters other than $k$. The algorithm is based on an appropriate grid search
over th... | computer science |
40,589 | Learning Equilibria in Games by Stochastic Distributed Algorithms | cs.GT | We consider a class of fully stochastic and fully distributed algorithms,
that we prove to learn equilibria in games.
Indeed, we consider a family of stochastic distributed dynamics that we prove
to converge weakly (in the sense of weak convergence for probabilistic
processes) towards their mean-field limit, i.e an o... | computer science |
40,590 | Network-aware Adaptation with Real-Time Channel Statistics for Wireless
LAN Multimedia Transmissions in the Digital Home | cs.NI | This paper suggests the use of intelligent network-aware processing agents in
wireless local area network drivers to generate metrics for bandwidth
estimation based on real-time channel statistics to enable wireless multimedia
application adaptation. Various configurations in the wireless digital home are
studied and t... | computer science |
40,591 | Contextual Bandits with Similarity Information | cs.DS | In a multi-armed bandit (MAB) problem, an online algorithm makes a sequence
of choices. In each round it chooses from a time-invariant set of alternatives
and receives the payoff associated with this alternative. While the case of
small strategy sets is by now well-understood, a lot of recent work has focused
on MAB pr... | computer science |
40,592 | Prediction of Zoonosis Incidence in Human using Seasonal Auto Regressive
Integrated Moving Average (SARIMA) | cs.LG | Zoonosis refers to the transmission of infectious diseases from animal to
human. The increasing number of zoonosis incidence makes the great losses to
lives, including humans and animals, and also the impact in social economic. It
motivates development of a system that can predict the future number of
zoonosis occurren... | computer science |
40,593 | Low-rank Matrix Completion with Noisy Observations: a Quantitative
Comparison | cs.LG | We consider a problem of significant practical importance, namely, the
reconstruction of a low-rank data matrix from a small subset of its entries.
This problem appears in many areas such as collaborative filtering, computer
vision and wireless sensor networks. In this paper, we focus on the matrix
completion problem i... | computer science |
40,594 | Strategies for online inference of model-based clustering in large and
growing networks | stat.AP | In this paper we adapt online estimation strategies to perform model-based
clustering on large networks. Our work focuses on two algorithms, the first
based on the SAEM algorithm, and the second on variational methods. These two
strategies are compared with existing approaches on simulated and real data. We
use the met... | computer science |
40,595 | On Learning Finite-State Quantum Sources | cs.LG | We examine the complexity of learning the distributions produced by
finite-state quantum sources. We show how prior techniques for learning hidden
Markov models can be adapted to the quantum generator model to find that the
analogous state of affairs holds: information-theoretically, a polynomial
number of samples suff... | computer science |
40,596 | A Gradient Descent Algorithm on the Grassman Manifold for Matrix
Completion | cs.NA | We consider the problem of reconstructing a low-rank matrix from a small
subset of its entries. In this paper, we describe the implementation of an
efficient algorithm called OptSpace, based on singular value decomposition
followed by local manifold optimization, for solving the low-rank matrix
completion problem. It h... | computer science |
40,597 | Multi-path Probabilistic Available Bandwidth Estimation through Bayesian
Active Learning | cs.NI | Knowing the largest rate at which data can be sent on an end-to-end path such
that the egress rate is equal to the ingress rate with high probability can be
very practical when choosing transmission rates in video streaming or selecting
peers in peer-to-peer applications. We introduce probabilistic available
bandwidth,... | computer science |
40,598 | Online Learning in Opportunistic Spectrum Access: A Restless Bandit
Approach | math.OC | We consider an opportunistic spectrum access (OSA) problem where the
time-varying condition of each channel (e.g., as a result of random fading or
certain primary users' activities) is modeled as an arbitrary finite-state
Markov chain. At each instance of time, a (secondary) user probes a channel and
collects a certain... | computer science |
40,599 | Converged Algorithms for Orthogonal Nonnegative Matrix Factorizations | cs.LG | This paper proposes uni-orthogonal and bi-orthogonal nonnegative matrix
factorization algorithms with robust convergence proofs. We design the
algorithms based on the work of Lee and Seung [1], and derive the converged
versions by utilizing ideas from the work of Lin [2]. The experimental results
confirm the theoretica... | computer science |
40,600 | Resource-bounded Dimension in Computational Learning Theory | cs.CC | This paper focuses on the relation between computational learning theory and
resource-bounded dimension. We intend to establish close connections between
the learnability/nonlearnability of a concept class and its corresponding size
in terms of effective dimension, which will allow the use of powerful dimension
techniq... | computer science |
40,601 | Efficient Minimization of Decomposable Submodular Functions | cs.LG | Many combinatorial problems arising in machine learning can be reduced to the
problem of minimizing a submodular function. Submodular functions are a natural
discrete analog of convex functions, and can be minimized in strongly
polynomial time. Unfortunately, state-of-the-art algorithms for general
submodular minimizat... | computer science |
40,602 | A Primal-Dual Convergence Analysis of Boosting | cs.LG | Boosting combines weak learners into a predictor with low empirical risk. Its
dual constructs a high entropy distribution upon which weak learners and
training labels are uncorrelated. This manuscript studies this primal-dual
relationship under a broad family of losses, including the exponential loss of
AdaBoost and th... | computer science |
40,603 | File Transfer Application For Sharing Femto Access | cs.NI | In wireless access network optimization, today's main challenges reside in
traffic offload and in the improvement of both capacity and coverage networks.
The operators are interested in solving their localized coverage and capacity
problems in areas where the macro network signal is not able to serve the
demand for mob... | computer science |
40,604 | Inference algorithms for pattern-based CRFs on sequence data | cs.LG | We consider Conditional Random Fields (CRFs) with pattern-based potentials
defined on a chain. In this model the energy of a string (labeling) $x_1...x_n$
is the sum of terms over intervals $[i,j]$ where each term is non-zero only if
the substring $x_i...x_j$ equals a prespecified pattern $\alpha$. Such CRFs can
be nat... | computer science |
40,605 | Learning from Collective Intelligence in Groups | cs.SI | Collective intelligence, which aggregates the shared information from large
crowds, is often negatively impacted by unreliable information sources with the
low quality data. This becomes a barrier to the effective use of collective
intelligence in a variety of applications. In order to address this issue, we
propose a ... | computer science |
40,606 | Sensory Anticipation of Optical Flow in Mobile Robotics | cs.RO | In order to anticipate dangerous events, like a collision, an agent needs to
make long-term predictions. However, those are challenging due to uncertainties
in internal and external variables and environment dynamics. A sensorimotor
model is acquired online by the mobile robot using a state-of-the-art method
that learn... | computer science |
40,607 | A Benchmark to Select Data Mining Based Classification Algorithms For
Business Intelligence And Decision Support Systems | cs.DB | DSS serve the management, operations, and planning levels of an organization
and help to make decisions, which may be rapidly changing and not easily
specified in advance. Data mining has a vital role to extract important
information to help in decision making of a decision support system.
Integration of data mining an... | computer science |
40,608 | Deterministic MDPs with Adversarial Rewards and Bandit Feedback | cs.GT | We consider a Markov decision process with deterministic state transition
dynamics, adversarially generated rewards that change arbitrarily from round to
round, and a bandit feedback model in which the decision maker only observes
the rewards it receives. In this setting, we present a novel and efficient
online decisio... | computer science |
40,609 | A Novel Learning Algorithm for Bayesian Network and Its Efficient
Implementation on GPU | cs.DC | Computational inference of causal relationships underlying complex networks,
such as gene-regulatory pathways, is NP-complete due to its combinatorial
nature when permuting all possible interactions. Markov chain Monte Carlo
(MCMC) has been introduced to sample only part of the combinations while still
guaranteeing con... | computer science |
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