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The minimum linear arrangement problem on a network consists of finding the minimum sum of edge lengths that can be achieved when the vertices are arranged linearly. Although there are algorithms to solve this problem on trees in polynomial…

Data Analysis, Statistics and Probability · Physics 2017-12-14 Juan Luis Esteban , Ramon Ferrer-i-Cancho , Carlos Gómez-Rodríguez

We study the complexity and expressive power of conjunctive queries over unranked labeled trees represented using a variety of structure relations such as ``child'', ``descendant'', and ``following'' as well as unary relations for node…

Databases · Computer Science 2007-05-23 Georg Gottlob , Christoph Koch , Klaus U. Schulz

Reduction trees are a way of encoding a substitution procedure dictated by the relations of an algebra. We use reduction trees in the subdivision algebra to construct canonical triangulations of flow polytopes which are shellable. We…

Combinatorics · Mathematics 2015-02-16 Karola Mészáros

In an impressive series of papers, Krivine showed at the edge of the last decade how classical realizability provides a surprising technique to build models for classical theories. In particular, he proved that classical realizability…

Logic in Computer Science · Computer Science 2020-07-16 Étienne Miquey

Discrete barycenters are the optimal solutions to mass transport problems for a set of discrete measures. Such transport problems arise in many applications of operations research and statistics. The best known algorithms for exact…

Optimization and Control · Mathematics 2019-04-24 Steffen Borgwardt , Stephan Patterson

The junction-tree representation provides an attractive structural property for organizing a decomposable graph. In this study, we present two novel stochastic algorithms, which we call the junction-tree expander and junction-tree collapser…

Statistics Theory · Mathematics 2021-02-16 Jimmy Olsson , Tetyana Pavlenko , Felix L. Rios

We consider N-fold 4-block decomposable integer programs, which simultaneously generalize N-fold integer programs and two-stage stochastic integer programs with N scenarios. In previous work [R. Hemmecke, M. Koeppe, R. Weismantel, A…

Optimization and Control · Mathematics 2017-01-03 Raymond Hemmecke , Matthias Köppe , Robert Weismantel

In sphere of research of discrete optimization algorithms efficiency the important place occupies a method of polynomial reducibility of some problems to others with use of special purpose components. In this paper a novel method of compact…

Data Structures and Algorithms · Computer Science 2013-09-25 V. F. Romanov

We investigate the representation of symmetric polynomials as a sum of squares. Since this task is solved using semidefinite programming tools we explore the geometric, algebraic, and computational implications of the presence of discrete…

Commutative Algebra · Mathematics 2007-05-23 Karin Gatermann , Pablo A. Parrilo

Extraction of structure, in particular of group symmetries, is increasingly crucial to understanding and building intelligent models. In particular, some information-theoretic models of parsimonious learning have been argued to induce…

Information Theory · Computer Science 2025-07-08 Hippolyte Charvin , Nicola Catenacci Volpi , Daniel Polani

We introduce an approach to training a given compact network. To this end, we leverage over-parameterization, which typically improves both neural network optimization and generalization. Specifically, we propose to expand each linear layer…

Computer Vision and Pattern Recognition · Computer Science 2021-04-15 Shuxuan Guo , Jose M. Alvarez , Mathieu Salzmann

This paper proposes a method for solving multivariate regression and classification problems using piecewise linear predictors over a polyhedral partition of the feature space. The resulting algorithm that we call PARC (Piecewise Affine…

Machine Learning · Computer Science 2021-03-11 Alberto Bemporad

We develop a theoretical framework for the analysis of oblique decision trees, where the splits at each decision node occur at linear combinations of the covariates (as opposed to conventional tree constructions that force axis-aligned…

Statistics Theory · Mathematics 2023-09-01 Matias D. Cattaneo , Rajita Chandak , Jason M. Klusowski

In this paper, we study the mixed-integer nonlinear set given by a separable quadratic constraint on continuous variables, where each continuous variable is controlled by an additional indicator. This set occurs pervasively in optimization…

Optimization and Control · Mathematics 2022-09-07 Andres Gomez , Weijun Xie

We propose a general approach for supervised learning with structured output spaces, such as combinatorial and polyhedral sets, that is based on minimizing estimated conditional risk functions. Given a loss function defined over pairs of…

Machine Learning · Statistics 2017-02-28 Chong Yang Goh , Patrick Jaillet

It is well-known that the convex and concave envelope of a multilinear polynomial over a box are polyhedral functions. Exponential-sized extended and projected formulations for these envelopes are also known. We consider the convexification…

Optimization and Control · Mathematics 2021-06-14 Yibo Xu , Warren Adams , Akshay Gupte

Circuits and extended formulations are classical concepts in linear programming theory. The circuits of a polyhedron are the elementary difference vectors between feasible points and include all edge directions. We study the connection…

Optimization and Control · Mathematics 2023-08-04 Steffen Borgwardt , Matthias Brugger

We study a class of integer bilevel programs with second-order cone constraints at the upper-level and a convex-quadratic objective function and linear constraints at the lower-level. We develop disjunctive cuts (DCs) to separate…

Optimization and Control · Mathematics 2023-06-06 Elisabeth Gaar , Jon Lee , Ivana Ljubić , Markus Sinnl , Kübra Tanınmış

This is a survey on tropical polytopes from the combinatorial point of view and with a focus on algorithms. Tropical convexity is interesting because it relates a number of combinatorial concepts including ordinary convexity, monomial…

Combinatorics · Mathematics 2008-10-12 Michael Joswig

In machine learning and neuroscience, certain computational structures and algorithms are known to yield disentangled representations without us understanding why, the most striking examples being perhaps convolutional neural networks and…

Machine Learning · Computer Science 2017-03-21 Gary Bécigneul