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Title: Rejoinder: Gibbs Sampling, Exponential Families and Orthogonal Polynomials |
Abstract: We are thankful to the discussants for their hard, interesting work. The main purpose of our paper was to give reasonably sharp rates of convergence for some simple examples of the Gibbs sampler. We chose examples from expository accounts where direct use of available techniques gave practically useless answe... |
Title: Open architecture for multilingual parallel texts |
Abstract: Multilingual parallel texts (abbreviated to parallel texts) are linguistic versions of the same content ("translations"); e.g., the Maastricht Treaty in English and Spanish are parallel texts. This document is about creating an open architecture for the whole Authoring, Translation and Publishing Chain (ATP-c... |
Title: Randomization Does Not Justify Logistic Regression |
Abstract: The logit model is often used to analyze experimental data. However, randomization does not justify the model, so the usual estimators can be inconsistent. A consistent estimator is proposed. Neyman's non-parametric setup is used as a benchmark. In this setup, each subject has two potential responses, one if ... |
Title: Hybrid data regression modelling in measurement |
Abstract: Measurement involves the determination of quantitative estimates of physical quantities from experiment, along with estimates of their associated uncertainties. Herewith an experimental system model is the key to extracting information from the experimental data. The measurement information obtained depends d... |
Title: Karl Pearson's Theoretical Errors and the Advances They Inspired |
Abstract: Karl Pearson played an enormous role in determining the content and organization of statistical research in his day, through his research, his teaching, his establishment of laboratories, and his initiation of a vast publishing program. His technical contributions had initially and continue today to have a pr... |
Title: A Conversation with Jayaram Sethuraman |
Abstract: Jayaram Sethuraman was born in the town of Hubli in Bombay Province (now Karnataka State) on October 3, 1937. His early years were spent in Hubli and in 1950 his family moved to Madras (now renamed Chennai). He graduated from Madras University in 1957 with a B.Sc. (Hons) degree in statistics and he earned his... |
Title: Sparse sampling: Spatial design for monitoring stream networks |
Abstract: Spatial designs for monitoring stream networks, especially ephemeral systems, are typically non-standard, `sparse' and can be very complex, reflecting the complexity of the ecosystem being monitored, the scale of the population, and the competing multiple monitoring objectives. The main purpose of this paper ... |
Title: Swapping Lemmas for Regular and Context-Free Languages |
Abstract: In formal language theory, one of the most fundamental tools, known as pumping lemmas, is extremely useful for regular and context-free languages. However, there are natural properties for which the pumping lemmas are of little use. One of such examples concerns a notion of advice, which depends only on the s... |
Title: A Variational Inference Framework for Soft-In-Soft-Out Detection in Multiple Access Channels |
Abstract: We propose a unified framework for deriving and studying soft-in-soft-out (SISO) detection in interference channels using the concept of variational inference. The proposed framework may be used in multiple-access interference (MAI), inter-symbol interference (ISI), and multiple-input multiple-outpu (MIMO) ch... |
Title: On the nature of long-range letter correlations in texts |
Abstract: The origin of long-range letter correlations in natural texts is studied using random walk analysis and Jensen-Shannon divergence. It is concluded that they result from slow variations in letter frequency distribution, which are a consequence of slow variations in lexical composition within the text. These co... |
Title: A Uniform Approach to Analogies, Synonyms, Antonyms, and Associations |
Abstract: Recognizing analogies, synonyms, antonyms, and associations appear to be four distinct tasks, requiring distinct NLP algorithms. In the past, the four tasks have been treated independently, using a wide variety of algorithms. These four semantic classes, however, are a tiny sample of the full range of semanti... |
Title: Bayesian Analysis of Value-at-Risk with Product Partition Models |
Abstract: In this paper we propose a novel Bayesian methodology for Value-at-Risk computation based on parametric Product Partition Models. Value-at-Risk is a standard tool to measure and control the market risk of an asset or a portfolio, and it is also required for regulatory purposes. Its popularity is partly due to... |
Title: Randomised Variable Neighbourhood Search for Multi Objective Optimisation |
Abstract: Various local search approaches have recently been applied to machine scheduling problems under multiple objectives. Their foremost consideration is the identification of the set of Pareto optimal alternatives. An important aspect of successfully solving these problems lies in the definition of an appropriate... |
Title: The Complexity of Enriched Mu-Calculi |
Abstract: The fully enriched μ-calculus is the extension of the propositional μ-calculus with inverse programs, graded modalities, and nominals. While satisfiability in several expressive fragments of the fully enriched μ-calculus is known to be decidable and ExpTime-complete, it has recently been proved that ... |
Title: Foundations of the Pareto Iterated Local Search Metaheuristic |
Abstract: The paper describes the proposition and application of a local search metaheuristic for multi-objective optimization problems. It is based on two main principles of heuristic search, intensification through variable neighborhoods, and diversification through perturbations and successive iterations in favorabl... |
Title: A Computational Study of Genetic Crossover Operators for Multi-Objective Vehicle Routing Problem with Soft Time Windows |
Abstract: The article describes an investigation of the effectiveness of genetic algorithms for multi-objective combinatorial optimization (MOCO) by presenting an application for the vehicle routing problem with soft time windows. The work is motivated by the question, if and how the problem structure influences the ef... |
Title: Genetic Algorithms for multiple objective vehicle routing |
Abstract: The talk describes a general approach of a genetic algorithm for multiple objective optimization problems. A particular dominance relation between the individuals of the population is used to define a fitness operator, enabling the genetic algorithm to adress even problems with efficient, but convex-dominated... |
Title: Quantum classification |
Abstract: Quantum classification is defined as the task of predicting the associated class of an unknown quantum state drawn from an ensemble of pure states given a finite number of copies of this state. By recasting the state discrimination problem within the framework of Machine Learning (ML), we can use the notion o... |
Title: The Stock Market as a Game: An Agent Based Approach to Trading in Stocks |
Abstract: Just as war is sometimes fallaciously represented as a zero sum game -- when in fact war is a negative sum game - stock market trading, a positive sum game over time, is often erroneously represented as a zero sum game. This is called the "zero sum fallacy" -- the erroneous belief that one trader in a stock m... |
Title: Agent Models of Political Interactions |
Abstract: Looks at state interactions from an agent based AI perspective to see state interactions as an example of emergent intelligent behavior. Exposes basic principles of game theory. |
Title: Principal Graphs and Manifolds |
Abstract: In many physical, statistical, biological and other investigations it is desirable to approximate a system of points by objects of lower dimension and/or complexity. For this purpose, Karl Pearson invented principal component analysis in 1901 and found 'lines and planes of closest fit to system of points'. Th... |
Title: From Data to the p-Adic or Ultrametric Model |
Abstract: We model anomaly and change in data by embedding the data in an ultrametric space. Taking our initial data as cross-tabulation counts (or other input data formats), Correspondence Analysis allows us to endow the information space with a Euclidean metric. We then model anomaly or change by an induced ultrametr... |
Title: A framework for the interactive resolution of multi-objective vehicle routing problems |
Abstract: The article presents a framework for the resolution of rich vehicle routing problems which are difficult to address with standard optimization techniques. We use local search on the basis on variable neighborhood search for the construction of the solutions, but embed the techniques in a flexible framework th... |
Title: An Alternating l1 approach to the compressed sensing problem |
Abstract: Compressed sensing is a new methodology for constructing sensors which allow sparse signals to be efficiently recovered using only a small number of observations. The recovery problem can often be stated as the one of finding the solution of an underdetermined system of linear equations with the smallest poss... |
Title: Improving Local Search for Fuzzy Scheduling Problems |
Abstract: The integration of fuzzy set theory and fuzzy logic into scheduling is a rather new aspect with growing importance for manufacturing applications, resulting in various unsolved aspects. In the current paper, we investigate an improved local search technique for fuzzy scheduling problems with fitness plateaus,... |
Title: Microcontroller-based System for Modular Networked Robot |
Abstract: A prototype of modular networked robot for autonomous monitoring works with full control over web through wireless connection has been developed. The robot is equipped with a particular set of built-in analyzing tools and appropriate censors, depending on its main purposes, to enable self-independent and real... |
Title: Proposition of the Interactive Pareto Iterated Local Search Procedure - Elements and Initial Experiments |
Abstract: The article presents an approach to interactively solve multi-objective optimization problems. While the identification of efficient solutions is supported by computational intelligence techniques on the basis of local search, the search is directed by partial preference information obtained from the decision... |
Title: Bin Packing Under Multiple Objectives - a Heuristic Approximation Approach |
Abstract: The article proposes a heuristic approximation approach to the bin packing problem under multiple objectives. In addition to the traditional objective of minimizing the number of bins, the heterogeneousness of the elements in each bin is minimized, leading to a biobjective formulation of the problem with a tr... |
Title: An application of the Threshold Accepting metaheuristic for curriculum based course timetabling |
Abstract: The article presents a local search approach for the solution of timetabling problems in general, with a particular implementation for competition track 3 of the International Timetabling Competition 2007 (ITC 2007). The heuristic search procedure is based on Threshold Accepting to overcome local optima. A st... |
Title: Peek Arc Consistency |
Abstract: This paper studies peek arc consistency, a reasoning technique that extends the well-known arc consistency technique for constraint satisfaction. In contrast to other more costly extensions of arc consistency that have been studied in the literature, peek arc consistency requires only linear space and quadrat... |
Title: Superposition for Fixed Domains |
Abstract: Superposition is an established decision procedure for a variety of first-order logic theories represented by sets of clauses. A satisfiable theory, saturated by superposition, implicitly defines a minimal term-generated model for the theory. Proving universal properties with respect to a saturated theory dir... |
Title: MOOPPS: An Optimization System for Multi Objective Scheduling |
Abstract: In the current paper, we present an optimization system solving multi objective production scheduling problems (MOOPPS). The identification of Pareto optimal alternatives or at least a close approximation of them is possible by a set of implemented metaheuristics. Necessary control parameters can easily be ad... |
Title: Least Squares and Shrinkage Estimation under Bimonotonicity Constraints |
Abstract: In this paper we describe active set type algorithms for minimization of a smooth function under general order constraints, an important case being functions on the set of bimonotone r-by-s matrices. These algorithms can be used, for instance, to estimate a bimonotone regression function via least squares or ... |
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