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Title: Online Learning: Beyond Regret |
Abstract: We study online learnability of a wide class of problems, extending the results of (Rakhlin, Sridharan, Tewari, 2010) to general notions of performance measure well beyond external regret. Our framework simultaneously captures such well-known notions as internal and general Phi-regret, learning with non-addit... |
Title: Tensor-SIFT based Earth Mover's Distance for Contour Tracking |
Abstract: Contour tracking in adverse environments is a challenging problem due to cluttered background, illumination variation, occlusion, and noise, among others. This paper presents a robust contour tracking method by contributing to some of the key issues involved, including (a) a region functional formulation and ... |
Title: The Data Replication Method for the Classification with Reject Option |
Abstract: Classification is one of the most important tasks of machine learning. Although the most well studied model is the two-class problem, in many scenarios there is the opportunity to label critical items for manual revision, instead of trying to automatically classify every item. In this paper we adapt a paradig... |
Title: Warping Peirce Quincuncial Panoramas |
Abstract: The Peirce quincuncial projection is a mapping of the surface of a sphere to the interior of a square. It is a conformal map except for four points on the equator. These points of non-conformality cause significant artifacts in photographic applications. In this paper, we propose an algorithm and user-interfa... |
Title: New Methods of Analysis of Narrative and Semantics in Support of Interactivity |
Abstract: Our work has focused on support for film or television scriptwriting. Since this involves potentially varied story-lines, we note the implicit or latent support for interactivity. Furthermore the film, television, games, publishing and other sectors are converging, so that cross-over and re-use of one form of... |
Title: "Meaning" as a sociological concept: A review of the modeling, mapping, and simulation of the communication of knowledge and meaning |
Abstract: The development of discursive knowledge presumes the communication of meaning as analytically different from the communication of information. Knowledge can then be considered as a meaning which makes a difference. Whereas the communication of information is studied in the information sciences and scientometr... |
Title: Integration of Flexible Web Based GUI in I-SOAS |
Abstract: It is necessary to improve the concepts of the present web based graphical user interface for the development of more flexible and intelligent interface to provide ease and increase the level of comfort at user end like most of the desktop based applications. This research is conducted targeting the goal of i... |
Title: Integration of Agile Ontology Mapping towards NLP Search in I-SOAS |
Abstract: In this research paper we address the importance of Product Data Management (PDM) with respect to its contributions in industry. Moreover we also present some currently available major challenges to PDM communities and targeting some of these challenges we present an approach i.e. I-SOAS, and briefly discuss ... |
Title: The Inverse Task of the Reflexive Game Theory: Theoretical Matters, Practical Applications and Relationship with Other Issues |
Abstract: The Reflexive Game Theory (RGT) has been recently proposed by Vladimir Lefebvre to model behavior of individuals in groups. The goal of this study is to introduce the Inverse task. We consider methods of solution together with practical applications. We present a brief overview of the RGT for easy understandi... |
Title: Prize insights in probability, and one goat of a recycled error: Jason Rosenhouse's The Monty Hall Problem |
Abstract: The Monty Hall problem is the TV game scenario where you, the contestant, are presented with three doors, with a car hidden behind one and goats hidden behind the other two. After you select a door, the host (Monty Hall) opens a second door to reveal a goat. You are then invited to stay with your original cho... |
Title: Learning Planar Ising Models |
Abstract: Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering. However, exact inference is intractable in general graphical models, which suggests the problem of seeking the best approximation to a coll... |
Title: A Probabilistic Approach for Learning Folksonomies from Structured Data |
Abstract: Learning structured representations has emerged as an important problem in many domains, including document and Web data mining, bioinformatics, and image analysis. One approach to learning complex structures is to integrate many smaller, incomplete and noisy structure fragments. In this work, we present an u... |
Title: Optimizing real-time RDF data streams |
Abstract: The Resource Description Framework (RDF) provides a common data model for the integration of "real-time" social and sensor data streams with the Web and with each other. While there exist numerous protocols and data formats for exchanging dynamic RDF data, or RDF updates, these options should be examined care... |
Title: Predictor-dependent shrinkage for linear regression via partial factor modeling |
Abstract: In prediction problems with more predictors than observations, it can sometimes be helpful to use a joint probability model, $\pi(Y,X)$, rather than a purely conditional model, $\pi(Y \mid X)$, where $Y$ is a scalar response variable and $X$ is a vector of predictors. This approach is motivated by the fact th... |
Title: PADDLE: Proximal Algorithm for Dual Dictionaries LEarning |
Abstract: Recently, considerable research efforts have been devoted to the design of methods to learn from data overcomplete dictionaries for sparse coding. However, learned dictionaries require the solution of an optimization problem for coding new data. In order to overcome this drawback, we propose an algorithm aime... |
Title: Characterization of differentially expressed genes using high-dimensional co-expression networks |
Abstract: We present a technique to characterize differentially expressed genes in terms of their position in a high-dimensional co-expression network. The set-up of Gaussian graphical models is used to construct representations of the co-expression network in such a way that redundancy and the propagation of spurious ... |
Title: Artificial Hormone Reaction Networks: Towards Higher Evolvability in Evolutionary Multi-Modular Robotics |
Abstract: The semi-automatic or automatic synthesis of robot controller software is both desirable and challenging. Synthesis of rather simple behaviors such as collision avoidance by applying artificial evolution has been shown multiple times. However, the difficulty of this synthesis increases heavily with increasing... |
Title: Modeling Image Structure with Factorized Phase-Coupled Boltzmann Machines |
Abstract: We describe a model for capturing the statistical structure of local amplitude and local spatial phase in natural images. The model is based on a recently developed, factorized third-order Boltzmann machine that was shown to be effective at capturing higher-order structure in images by modeling dependencies a... |
Title: Supervised Random Walks: Predicting and Recommending Links in Social Networks |
Abstract: Predicting the occurrence of links is a fundamental problem in networks. In the link prediction problem we are given a snapshot of a network and would like to infer which interactions among existing members are likely to occur in the near future or which existing interactions are we missing. Although this pro... |
Title: An Introduction to Conditional Random Fields |
Abstract: Often we wish to predict a large number of variables that depend on each other as well as on other observed variables. Structured prediction methods are essentially a combination of classification and graphical modeling, combining the ability of graphical models to compactly model multivariate data with the a... |
Title: Clustering and Latent Semantic Indexing Aspects of the Singular Value Decomposition |
Abstract: This paper discusses clustering and latent semantic indexing (LSI) aspects of the singular value decomposition (SVD). The purpose of this paper is twofold. The first is to give an explanation on how and why the singular vectors can be used in clustering. And the second is to show that the two seemingly unrela... |
Title: Motifs de graphe pour le calcul de d\'ependances syntaxiques compl\`etes |
Abstract: This article describes a method to build syntactical dependencies starting from the phrase structure parsing process. The goal is to obtain all the information needed for a detailled semantical analysis. Interaction Grammars are used for parsing; the saturation of polarities which is the core of this formalis... |
Title: A Fuzzy Clustering Model for Fuzzy Data with Outliers |
Abstract: In this paper a fuzzy clustering model for fuzzy data with outliers is proposed. The model is based on Wasserstein distance between interval valued data which is generalized to fuzzy data. In addition, Keller's approach is used to identify outliers and reduce their influences. We have also defined a transform... |
Title: Sparse Choice Models |
Abstract: Choice models, which capture popular preferences over objects of interest, play a key role in making decisions whose eventual outcome is impacted by human choice behavior. In most scenarios, the choice model, which can effectively be viewed as a distribution over permutations, must be learned from observed da... |
Title: Should one compute the Temporal Difference fix point or minimize the Bellman Residual? The unified oblique projection view |
Abstract: We investigate projection methods, for evaluating a linear approximation of the value function of a policy in a Markov Decision Process context. We consider two popular approaches, the one-step Temporal Difference fix-point computation (TD(0)) and the Bellman Residual (BR) minimization. We describe examples, ... |
Title: Robust adaptive Metropolis algorithm with coerced acceptance rate |
Abstract: The adaptive Metropolis (AM) algorithm of Haario, Saksman and Tamminen [Bernoulli 7 (2001) 223-242] uses the estimated covariance of the target distribution in the proposal distribution. This paper introduces a new robust adaptive Metropolis algorithm estimating the shape of the target distribution and simult... |
Title: Graphical Comparison of MCMC Performance |
Abstract: This paper presents a graphical method for comparing performance of Markov Chain Monte Carlo methods. Most researchers present comparisons of MCMC methods using tables of figures of merit; this paper presents a graphical alternative. It first discusses the computation of autocorrelation time, then uses this t... |
Title: An Alternating Direction Method for Finding Dantzig Selectors |
Abstract: In this paper, we study the alternating direction method for finding the Dantzig selectors, which are first introduced in [8]. In particular, at each iteration we apply the nonmonotone gradient method proposed in [17] to approximately solve one subproblem of this method. We compare our approach with a first-o... |
Title: Generalized Tree-Based Wavelet Transform |
Abstract: In this paper we propose a new wavelet transform applicable to functions defined on graphs, high dimensional data and networks. The proposed method generalizes the Haar-like transform proposed in [1], and it is defined via a hierarchical tree, which is assumed to capture the geometry and structure of the inpu... |
Title: Opinion Polarity Identification through Adjectives |
Abstract: "What other people think" has always been an important piece of information during various decision-making processes. Today people frequently make their opinions available via the Internet, and as a result, the Web has become an excellent source for gathering consumer opinions. There are now numerous Web reso... |
Title: Random Projections for $k$-means Clustering |
Abstract: This paper discusses the topic of dimensionality reduction for $k$-means clustering. We prove that any set of $n$ points in $d$ dimensions (rows in a matrix $A \in \RR^n \times d$) can be projected into $t = \Omega(k / \eps^2)$ dimensions, for any $\eps \in (0,1/3)$, in $O(n d \lceil \eps^-2 k/ \log(d) \rceil... |
Title: Stochastic blockmodels with growing number of classes |
Abstract: We present asymptotic and finite-sample results on the use of stochastic blockmodels for the analysis of network data. We show that the fraction of misclassified network nodes converges in probability to zero under maximum likelihood fitting when the number of classes is allowed to grow as the root of the net... |
Title: Slice Sampling with Adaptive Multivariate Steps: The Shrinking-Rank Method |
Abstract: The shrinking rank method is a variation of slice sampling that is efficient at sampling from multivariate distributions with highly correlated parameters. It requires that the gradient of the log-density be computable. At each individual step, it approximates the current slice with a Gaussian occupying a shr... |
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