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Related papers: Selection principles in mathematics: A milestone o…

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After discussing two senses in which the notion of undecidability is used, we present a survey of undecidable decision problems arising in various branches of mathematics.

Logic · Mathematics 2017-04-03 Bjorn Poonen

In this work we present a review of the state of the art of information theoretic feature selection methods. The concepts of feature relevance, redundance and complementarity (synergy) are clearly defined, as well as Markov blanket. The…

Machine Learning · Computer Science 2015-09-28 Jorge R. Vergara , Pablo A. Estévez

It was recently shown that the theory of linear stochastic systems can be viewed as a particular case of the theory of linear systems on a certain commutative ring of power series in a countable number of variables. In the present work we…

Functional Analysis · Mathematics 2011-04-11 Daniel Alpay , Haim Attia

The emergent field of probabilistic numerics has thus far lacked clear statistical principals. This paper establishes Bayesian probabilistic numerical methods as those which can be cast as solutions to certain inverse problems within the…

Methodology · Statistics 2019-11-15 Jon Cockayne , Chris Oates , Tim Sullivan , Mark Girolami

A selection of open problems in the theory of composites is presented. Particular attention is drawn to the question of whether two-dimensional, two-phase, composites with general geometries have the same set of possible effective tensors…

Analysis of PDEs · Mathematics 2021-06-09 Graeme W. Milton

We discuss general models of resource-sharing computations, with emphasis on the combinatorial structures and concepts that underlie the various deadlock models that have been proposed, the design of algorithms and deadlock-handling…

Operating Systems · Computer Science 2016-09-14 V. C. Barbosa

Determinantal point processes (DPPs) offer a powerful approach to modeling diversity in many applications where the goal is to select a diverse subset. We study the problem of learning the parameters (the kernel matrix) of a DPP from…

Machine Learning · Statistics 2014-11-10 Boqing Gong , Wei-lun Chao , Kristen Grauman , Fei Sha

We define lifting properties for universal algebras, which we study in this general context and then particularize to various such properties in certain classes of algebras. Next we focus on residuated lattices, in which we investigate…

Logic · Mathematics 2016-08-14 Daniela Cheptea , George Georgescu , Claudia Mureşan

We develop a unified framework for the study of properties involving diagonalizations of dense families in topological spaces. We provide complete classification of these properties. Our classification draws upon a large number of methods…

General Topology · Mathematics 2012-07-31 Maddalena Bonanzinga , Filippo Cammaroto , Bruno Antonio Pansera , Boaz Tsaban

We focus on two central themes in this dissertation. The first one is on decomposing polytopes and polynomials in ways that allow us to perform nonlinear optimization. We start off by explaining important results on decomposing a polytope…

Combinatorics · Mathematics 2016-05-18 Brandon Dutra

I discuss the historical roots of the landscape problem and propose criteria for its successful resolution. This provides a perspective to evaluate the possibility to solve it in several of the speculative cosmological scenarios under study…

History and Philosophy of Physics · Physics 2015-06-04 Lee Smolin

In this paper, a model for understanding the effects of selection using systems- level computational approaches is introduced. A number of concepts and principles essential for understanding the motivation for constructing the model will be…

Populations and Evolution · Quantitative Biology 2009-03-04 Bradly Alicea

Manifold optimization is ubiquitous in computational and applied mathematics, statistics, engineering, machine learning, physics, chemistry and etc. One of the main challenges usually is the non-convexity of the manifold constraints. By…

Optimization and Control · Mathematics 2019-06-14 Jiang Hu , Xin Liu , Zaiwen Wen , Yaxiang Yuan

The aim of this paper is twofold. First, three theoretical principles are formalized: randomization, overrepresentation and restriction. We develop these principles and give a rationale for their use in choosing the sampling design in a…

Methodology · Statistics 2016-12-16 Yves Tillé , Matthieu Wilhelm

This chapter delves into the realm of computational complexity, exploring the world of challenging combinatorial problems and their ties with statistical physics. Our exploration starts by delving deep into the foundations of combinatorial…

Disordered Systems and Neural Networks · Physics 2023-10-04 Raffaele Marino

Computational Social Choice is an interdisciplinary research area involving Economics, Political Science, and Social Science on the one side, and Mathematics and Computer Science (including Artificial Intelligence and Multiagent Systems) on…

Multiagent Systems · Computer Science 2014-07-09 Robert Bredereck , Jiehua Chen , Piotr Faliszewski , Jiong Guo , Rolf Niedermeier , Gerhard J. Woeginger

We study some closure-type properties of function spaces endowed with the new topology of strong uniform convergence on a bornology introduced by Beer and Levy in 2009. The study of these function spaces was initiated in [2] and [3]. The…

General Topology · Mathematics 2010-10-19 Agata Caserta , Giuseppe Di Maio , Ljubisa D. R. Kocinac

We present some variations on some of the main open problems on character degrees. We collect some of the methods that have proven to be very useful to work on these problems. These methods are also useful to solve certain problems on zeros…

Group Theory · Mathematics 2022-09-20 Alexander Moretó

This habilitation thesis is intended to be a good introduction to enumeration, the problem of listing solutions. It focuses on the different ways of measuring complexity in enumeration, with a particular emphasis on my contributions to the…

Computational Complexity · Computer Science 2023-10-02 Yann Strozecki

We deliver a call to arms for probabilistic numerical methods: algorithms for numerical tasks, including linear algebra, integration, optimization and solving differential equations, that return uncertainties in their calculations. Such…

Numerical Analysis · Mathematics 2016-02-17 Philipp Hennig , Michael A Osborne , Mark Girolami
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