text stringlengths 0 4.09k |
|---|
Title: An elementary approach to extreme values theory |
Abstract: This note presents a rather intuitive approach to extreme value theory. This approach was devised mostly for pedagogical reason. |
Title: A Bayesian Framework for Collaborative Multi-Source Signal Detection |
Abstract: This paper introduces a Bayesian framework to detect multiple signals embedded in noisy observations from a sensor array. For various states of knowledge on the communication channel and the noise at the receiving sensors, a marginalization procedure based on recent tools of finite random matrix theory, in co... |
Title: Distributed Constrained Optimization with Semicoordinate Transformations |
Abstract: Recent work has shown how information theory extends conventional full-rationality game theory to allow bounded rational agents. The associated mathematical framework can be used to solve constrained optimization problems. This is done by translating the problem into an iterated game, where each agent control... |
Title: \'Etude longitudinale d'une proc\'edure de mod\'elisation de connaissances en mati\`ere de gestion du territoire agricole |
Abstract: This paper gives an introduction to this issue, and presents the framework and the main steps of the Rosa project. Four teams of researchers, agronomists, computer scientists, psychologists and linguists were involved during five years within this project that aimed at the development of a knowledge based sys... |
Title: Mining Complex Hydrobiological Data with Galois Lattices |
Abstract: We have used Galois lattices for mining hydrobiological data. These data are about macrophytes, that are macroscopic plants living in water bodies. These plants are characterized by several biological traits, that own several modalities. Our aim is to cluster the plants according to their common traits and mo... |
Title: Statistical ranking and combinatorial Hodge theory |
Abstract: We propose a number of techniques for obtaining a global ranking from data that may be incomplete and imbalanced -- characteristics almost universal to modern datasets coming from e-commerce and internet applications. We are primarily interested in score or rating-based cardinal data. From raw ranking data, w... |
Title: Improved Estimation of High-dimensional Ising Models |
Abstract: We consider the problem of jointly estimating the parameters as well as the structure of binary valued Markov Random Fields, in contrast to earlier work that focus on one of the two problems. We formulate the problem as a maximization of $\ell_1$-regularized surrogate likelihood that allows us to find a spars... |
Title: Adaptive Base Class Boost for Multi-class Classification |
Abstract: We develop the concept of ABC-Boost (Adaptive Base Class Boost) for multi-class classification and present ABC-MART, a concrete implementation of ABC-Boost. The original MART (Multiple Additive Regression Trees) algorithm has been very successful in large-scale applications. For binary classification, ABC-MAR... |
Title: The Application of Fuzzy Logic to Collocation Extraction |
Abstract: Collocations are important for many tasks of Natural language processing such as information retrieval, machine translation, computational lexicography etc. So far many statistical methods have been used for collocation extraction. Almost all the methods form a classical crisp set of collocation. We propose a... |
Title: Optimal sequential multiple hypothesis tests |
Abstract: This work deals with a general problem of testing multiple hypotheses about the distribution of a discrete-time stochastic process. Both the Bayesian and the conditional settings are considered. The structure of optimal sequential tests is characterized. |
Title: Modeling Social Annotation: a Bayesian Approach |
Abstract: Collaborative tagging systems, such as Delicious, CiteULike, and others, allow users to annotate resources, e.g., Web pages or scientific papers, with descriptive labels called tags. The social annotations contributed by thousands of users, can potentially be used to infer categorical knowledge, classify docu... |
Title: Modeling Microscopic Chemical Sensors in Capillaries |
Abstract: Nanotechnology-based microscopic robots could provide accurate in vivo measurement of chemicals in the bloodstream for detailed biological research and as an aid to medical treatment. Quantitative performance estimates of such devices require models of how chemicals in the blood diffuse to the devices. This p... |
Title: Markov switching negative binomial models: an application to vehicle accident frequencies |
Abstract: In this paper, two-state Markov switching models are proposed to study accident frequencies. These models assume that there are two unobserved states of roadway safety, and that roadway entities (roadway segments) can switch between these states over time. The states are distinct, in the sense that in the dif... |
Title: Airport Gate Assignment: New Model and Implementation |
Abstract: Airport gate assignment is of great importance in airport operations. In this paper, we study the Airport Gate Assignment Problem (AGAP), propose a new model and implement the model with Optimization Programming language (OPL). With the objective to minimize the number of conflicts of any two adjacent aircraf... |
Title: Stability Bound for Stationary Phi-mixing and Beta-mixing Processes |
Abstract: Most generalization bounds in learning theory are based on some measure of the complexity of the hypothesis class used, independently of any algorithm. In contrast, the notion of algorithmic stability can be used to derive tight generalization bounds that are tailored to specific learning algorithms by exploi... |
Title: Artificial Intelligence Techniques for Steam Generator Modelling |
Abstract: This paper investigates the use of different Artificial Intelligence methods to predict the values of several continuous variables from a Steam Generator. The objective was to determine how the different artificial intelligence methods performed in making predictions on the given dataset. The artificial intel... |
Title: Robust Regression and Lasso |
Abstract: Lasso, or $\ell^1$ regularized least squares, has been explored extensively for its remarkable sparsity properties. It is shown in this paper that the solution to Lasso, in addition to its sparsity, has robustness properties: it is the solution to a robust optimization problem. This has two important conseque... |
Title: Necessary Conditions for Discontinuities of Multidimensional Size Functions |
Abstract: Some new results about multidimensional Topological Persistence are presented, proving that the discontinuity points of a k-dimensional size function are necessarily related to the pseudocritical or special values of the associated measuring function. |
Title: Action Theory Evolution |
Abstract: Like any other logical theory, domain descriptions in reasoning about actions may evolve, and thus need revision methods to adequately accommodate new information about the behavior of actions. The present work is about changing action domain descriptions in propositional dynamic logic. Its contribution is th... |
Title: The Expressive Power of Binary Submodular Functions |
Abstract: It has previously been an open problem whether all Boolean submodular functions can be decomposed into a sum of binary submodular functions over a possibly larger set of variables. This problem has been considered within several different contexts in computer science, including computer vision, artificial int... |
Title: Land Cover Mapping Using Ensemble Feature Selection Methods |
Abstract: Ensemble classification is an emerging approach to land cover mapping whereby the final classification output is a result of a consensus of classifiers. Intuitively, an ensemble system should consist of base classifiers which are diverse i.e. classifiers whose decision boundaries err differently. In this pape... |
Title: A Multivariate Regression Approach to Association Analysis of Quantitative Trait Network |
Abstract: Many complex disease syndromes such as asthma consist of a large number of highly related, rather than independent, clinical phenotypes, raising a new technical challenge in identifying genetic variations associated simultaneously with correlated traits. In this study, we propose a new statistical framework c... |
Title: P-values for high-dimensional regression |
Abstract: Assigning significance in high-dimensional regression is challenging. Most computationally efficient selection algorithms cannot guard against inclusion of noise variables. Asymptotically valid p-values are not available. An exception is a recent proposal by Wasserman and Roeder (2008) which splits the data i... |
Title: Modeling Cultural Dynamics |
Abstract: EVOC (for EVOlution of Culture) is a computer model of culture that enables us to investigate how various factors such as barriers to cultural diffusion, the presence and choice of leaders, or changes in the ratio of innovation to imitation affect the diversity and effectiveness of ideas. It consists of neura... |
Title: The "north pole problem" and random orthogonal matrices |
Abstract: This paper is motivated by the following observation. Take a 3 x 3 random (Haar distributed) orthogonal matrix $\Gamma$, and use it to "rotate" the north pole, $x_0$ say, on the unit sphere in $R^3$. This then gives a point $u=\Gamma x_0$ that is uniformly distributed on the unit sphere. Now use the same orth... |
Title: An Algorithm for Unconstrained Quadratically Penalized Convex Optimization |
Abstract: A descent algorithm, "Quasi-Quadratic Minimization with Memory" (QQMM), is proposed for unconstrained minimization of the sum, $F$, of a non-negative convex function, $V$, and a quadratic form. Such problems come up in regularized estimation in machine learning and statistics. In addition to values of $F$, QQ... |
Title: Exact phase transition of backtrack-free search with implications on the power of greedy algorithms |
Abstract: Backtracking is a basic strategy to solve constraint satisfaction problems (CSPs). A satisfiable CSP instance is backtrack-free if a solution can be found without encountering any dead-end during a backtracking search, implying that the instance is easy to solve. We prove an exact phase transition of backtrac... |
Title: Deformed Statistics Formulation of the Information Bottleneck Method |
Abstract: The theoretical basis for a candidate variational principle for the information bottleneck (IB) method is formulated within the ambit of the generalized nonadditive statistics of Tsallis. Given a nonadditivity parameter $ q $, the role of the of nonadditive statistics ($ q^*=2-q $) in relating Tsallis entropi... |
Title: Faster Retrieval with a Two-Pass Dynamic-Time-Warping Lower Bound |
Abstract: The Dynamic Time Warping (DTW) is a popular similarity measure between time series. The DTW fails to satisfy the triangle inequality and its computation requires quadratic time. Hence, to find closest neighbors quickly, we use bounding techniques. We can avoid most DTW computations with an inexpensive lower b... |
Title: chi2TeX Semi-automatic translation from chiwriter to LaTeX |
Abstract: Semi-automatic translation of math-filled book from obsolete ChiWriter format to LaTeX. Is it possible? Idea of criterion whether to use automatic or hand mode for translation. Illustrations. |
Title: On the computation of classical, boolean and free cumulants |
Abstract: This paper introduces a simple and computationally efficient algorithm for conversion formulae between moments and cumulants. The algorithm provides just one formula for classical, boolean and free cumulants. This is realized by using a suitable polynomial representation of Abel polynomials. The algorithm rel... |
Title: Approximate Bayesian computation (ABC) gives exact results under the assumption of model error |
Abstract: Approximate Bayesian computation (ABC) or likelihood-free inference algorithms are used to find approximations to posterior distributions without making explicit use of the likelihood function, depending instead on simulation of sample data sets from the model. In this paper we show that under the assumption ... |
Title: Kernel Regression by Mode Calculation of the Conditional Probability Distribution |
Abstract: The most direct way to express arbitrary dependencies in datasets is to estimate the joint distribution and to apply afterwards the argmax-function to obtain the mode of the corresponding conditional distribution. This method is in practice difficult, because it requires a global optimization of a complicated... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.