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Title: Robust Retrospective Multiple Change-point Estimation for Multivariate Data |
Abstract: We propose a non-parametric statistical procedure for detecting multiple change-points in multidimensional signals. The method is based on a test statistic that generalizes the well-known Kruskal-Wallis procedure to the multivariate setting. The proposed approach does not require any knowledge about the distr... |
Title: Proposing LT based Search in PDM Systems for Better Information Retrieval |
Abstract: PDM Systems contain and manage heavy amount of data but the search mechanism of most of the systems is not intelligent which can process user"s natural language based queries to extract desired information. Currently available search mechanisms in almost all of the PDM systems are not very efficient and based... |
Title: From Machine Learning to Machine Reasoning |
Abstract: A plausible definition of "reasoning" could be "algebraically manipulating previously acquired knowledge in order to answer a new question". This definition covers first-order logical inference or probabilistic inference. It also includes much simpler manipulations commonly used to build large learning system... |
Title: Optimal Synthesis for Nonholonomic Vehicles With Constrained Side Sensors |
Abstract: We present a complete characterization of shortest paths to a goal position for a vehicle with unicycle kinematics and a limited range sensor, constantly keeping a given landmark in sight. Previous work on this subject studied the optimal paths in case of a frontal, symmetrically limited Field--Of--View (FOV)... |
Title: Ologs: a categorical framework for knowledge representation |
Abstract: In this paper we introduce the olog, or ontology log, a category-theoretic model for knowledge representation (KR). Grounded in formal mathematics, ologs can be rigorously formulated and cross-compared in ways that other KR models (such as semantic networks) cannot. An olog is similar to a relational database... |
Title: Toward a Classification of Finite Partial-Monitoring Games |
Abstract: Partial-monitoring games constitute a mathematical framework for sequential decision making problems with imperfect feedback: The learner repeatedly chooses an action, opponent responds with an outcome, and then the learner suffers a loss and receives a feedback signal, both of which are fixed functions of th... |
Title: How the result of graph clustering methods depends on the construction of the graph |
Abstract: We study the scenario of graph-based clustering algorithms such as spectral clustering. Given a set of data points, one first has to construct a graph on the data points and then apply a graph clustering algorithm to find a suitable partition of the graph. Our main question is if and how the construction of t... |
Title: Improving DPLL Solver Performance with Domain-Specific Heuristics: the ASP Case |
Abstract: In spite of the recent improvements in the performance of the solvers based on the DPLL procedure, it is still possible for the search algorithm to focus on the wrong areas of the search space, preventing the solver from returning a solution in an acceptable amount of time. This prospect is a real concern e.g... |
Title: CLTs and asymptotic variance of time-sampled Markov chains |
Abstract: For a Markov transition kernel $P$ and a probability distribution $ \mu$ on nonnegative integers, a time-sampled Markov chain evolves according to the transition kernel $P_\mu = \sum_k \mu(k)P^k.$ In this note we obtain CLT conditions for time-sampled Markov chains and derive a spectral formula for the asympt... |
Title: Linear Temporal Logic and Propositional Schemata, Back and Forth (extended version) |
Abstract: This paper relates the well-known Linear Temporal Logic with the logic of propositional schemata introduced by the authors. We prove that LTL is equivalent to a class of schemata in the sense that polynomial-time reductions exist from one logic to the other. Some consequences about complexity are given. We re... |
Title: Malagasy Dialects and the Peopling of Madagascar |
Abstract: The origin of Malagasy DNA is half African and half Indonesian, nevertheless the Malagasy language, spoken by the entire population, belongs to the Austronesian family. The language most closely related to Malagasy is Maanyan (Greater Barito East group of the Austronesian family), but related languages are al... |
Title: A Constrained L1 Minimization Approach to Sparse Precision Matrix Estimation |
Abstract: A constrained L1 minimization method is proposed for estimating a sparse inverse covariance matrix based on a sample of $n$ iid $p$-variate random variables. The resulting estimator is shown to enjoy a number of desirable properties. In particular, it is shown that the rate of convergence between the estimato... |
Title: Adaptive Thresholding for Sparse Covariance Matrix Estimation |
Abstract: In this paper we consider estimation of sparse covariance matrices and propose a thresholding procedure which is adaptive to the variability of individual entries. The estimators are fully data driven and enjoy excellent performance both theoretically and numerically. It is shown that the estimators adaptivel... |
Title: Matrix completion with column manipulation: Near-optimal sample-robustness-rank tradeoffs |
Abstract: This paper considers the problem of matrix completion when some number of the columns are completely and arbitrarily corrupted, potentially by a malicious adversary. It is well-known that standard algorithms for matrix completion can return arbitrarily poor results, if even a single column is corrupted. One d... |
Title: On Oblivious PTAS's for Nash Equilibrium |
Abstract: If a game has a Nash equilibrium with probability values that are either zero or Omega(1) then this equilibrium can be found exhaustively in polynomial time. Somewhat surprisingly, we show that there is a PTAS for the games whose equilibria are guaranteed to have small-O(1/n)-values, and therefore large-Omega... |
Title: Modelling time to event with observations made at arbitrary times |
Abstract: We introduce new methods of analysing time to event data via extended versions of the proportional hazards and accelerated failure time (AFT) models. In many time to event studies, the time of first observation is arbitrary, in the sense that no risk modifying event occurs. This is particularly common in epid... |
Title: Opinions within Media, Power and Gossip |
Abstract: Despite the increasing diffusion of the Internet technology, TV remains the principal medium of communication. People's perceptions, knowledge, beliefs and opinions about matter of facts get (in)formed through the information reported on by the mass-media. However, a single source of information (and consensu... |
Title: A Comparison of Two Human Brain Tumor Segmentation Methods for MRI Data |
Abstract: The most common primary brain tumors are gliomas, evolving from the cerebral supportive cells. For clinical follow-up, the evaluation of the preoperative tumor volume is essential. Volumetric assessment of tumor volume with manual segmentation of its outlines is a time-consuming process that can be overcome w... |
Title: Universal Learning Theory |
Abstract: This encyclopedic article gives a mini-introduction into the theory of universal learning, founded by Ray Solomonoff in the 1960s and significantly developed and extended in the last decade. It explains the spirit of universal learning, but necessarily glosses over technical subtleties. |
Title: Algorithmic Randomness as Foundation of Inductive Reasoning and Artificial Intelligence |
Abstract: This article is a brief personal account of the past, present, and future of algorithmic randomness, emphasizing its role in inductive inference and artificial intelligence. It is written for a general audience interested in science and philosophy. Intuitively, randomness is a lack of order or predictability.... |
Title: The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond |
Abstract: This paper presents a finite-time analysis of the KL-UCB algorithm, an online, horizon-free index policy for stochastic bandit problems. We prove two distinct results: first, for arbitrary bounded rewards, the KL-UCB algorithm satisfies a uniformly better regret bound than UCB or UCB2; second, in the special ... |
Title: Multicriteria Steiner Tree Problem for Communication Network |
Abstract: This paper addresses combinatorial optimization scheme for solving the multicriteria Steiner tree problem for communication network topology design (e.g., wireless mesh network). The solving scheme is based on several models: multicriteria ranking, clustering, minimum spanning tree, and minimum Steiner tree p... |
Title: Guaranteeing Convergence of Iterative Skewed Voting Algorithms for Image Segmentation |
Abstract: In this paper we provide rigorous proof for the convergence of an iterative voting-based image segmentation algorithm called Active Masks. Active Masks (AM) was proposed to solve the challenging task of delineating punctate patterns of cells from fluorescence microscope images. Each iteration of AM consists o... |
Title: Online Least Squares Estimation with Self-Normalized Processes: An Application to Bandit Problems |
Abstract: The analysis of online least squares estimation is at the heart of many stochastic sequential decision making problems. We employ tools from the self-normalized processes to provide a simple and self-contained proof of a tail bound of a vector-valued martingale. We use the bound to construct a new tighter con... |
Title: Chernoff information of exponential families |
Abstract: Chernoff information upper bounds the probability of error of the optimal Bayesian decision rule for $2$-class classification problems. However, it turns out that in practice the Chernoff bound is hard to calculate or even approximate. In statistics, many usual distributions, such as Gaussians, Poissons or fr... |
Title: Decision Theory with Prospect Interference and Entanglement |
Abstract: We present a novel variant of decision making based on the mathematical theory of separable Hilbert spaces. This mathematical structure captures the effect of superposition of composite prospects, including many incorporated intentions, which allows us to describe a variety of interesting fallacies and anomal... |
Title: A General Framework for Development of the Cortex-like Visual Object Recognition System: Waves of Spikes, Predictive Coding and Universal Dictionary of Features |
Abstract: This study is focused on the development of the cortex-like visual object recognition system. We propose a general framework, which consists of three hierarchical levels (modules). These modules functionally correspond to the V1, V4 and IT areas. Both bottom-up and top-down connections between the hierarchica... |
Title: Feature selection via simultaneous sparse approximation for person specific face verification |
Abstract: There is an increasing use of some imperceivable and redundant local features for face recognition. While only a relatively small fraction of them is relevant to the final recognition task, the feature selection is a crucial and necessary step to select the most discriminant ones to obtain a compact face repr... |
Title: Feature Selection via Sparse Approximation for Face Recognition |
Abstract: Inspired by biological vision systems, the over-complete local features with huge cardinality are increasingly used for face recognition during the last decades. Accordingly, feature selection has become more and more important and plays a critical role for face data description and recognition. In this paper... |
Title: Multi-task GLOH feature selection for human age estimation |
Abstract: In this paper, we propose a novel age estimation method based on GLOH feature descriptor and multi-task learning (MTL). The GLOH feature descriptor, one of the state-of-the-art feature descriptor, is used to capture the age-related local and spatial information of face image. As the exacted GLOH features are ... |
Title: A Hierarchical Model for Aggregated Functional Data |
Abstract: In many areas of science one aims to estimate latent sub-population mean curves based only on observations of aggregated population curves. By aggregated curves we mean linear combination of functional data that cannot be observed individually. We assume that several aggregated curves with linear independent ... |
Title: Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies |
Abstract: Many practical studies rely on hypothesis testing procedures applied to data sets with missing information. An important part of the analysis is to determine the impact of the missing data on the performance of the test, and this can be done by properly quantifying the relative (to complete data) amount of av... |
Title: Transductive Ordinal Regression |
Abstract: Ordinal regression is commonly formulated as a multi-class problem with ordinal constraints. The challenge of designing accurate classifiers for ordinal regression generally increases with the number of classes involved, due to the large number of labeled patterns that are needed. The availability of ordinal ... |
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