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We develop the general form of the variational multiscale method in a discontinuous Galerkin framework. Our method is based on the decomposition of the true solution into discontinuous coarse-scale and discontinuous fine-scale parts. The…

Numerical Analysis · Mathematics 2017-09-20 Stein K. F. Stoter , Sergio R. Turteltaub , Steven J. Hulshoff , Dominik Schillinger

Frequent itemsets form a polytope and can be found and analyzed with Linear Programming.

Databases · Computer Science 2020-08-03 Natalia Vanetik

This work introduces a framework to address the computational complexity inherent in Mixed-Integer Programming (MIP) models by harnessing the potential of deep learning. By employing deep learning, we construct problem-specific heuristics…

Optimization and Control · Mathematics 2024-05-13 Niki Triantafyllou , Maria M. Papathanasiou

A novel formulation and training procedure for full Boltzmann machines in terms of a mixed binary quadratic feasibility problem is given. As a proof of concept, the theory is analytically and numerically tested on XOR patterns.

Machine Learning · Computer Science 2020-01-22 Arturo Berrones-Santos

An integer sequence that is defined by initial values and a linear recurrence with constant integer coefficients, can be represented by the difference of two arithmetic terms containing exponentiation. All constants occuring in the term are…

Number Theory · Mathematics 2024-06-11 Mihai Prunescu

We tackle the problems of latent variables identification and ``out-of-support'' image generation in representation learning. We show that both are possible for a class of decoders that we call additive, which are reminiscent of decoders…

Machine Learning · Computer Science 2023-11-03 Sébastien Lachapelle , Divyat Mahajan , Ioannis Mitliagkas , Simon Lacoste-Julien

Inverse optimization, determining parameters of an optimization problem that render a given solution optimal, has received increasing attention in recent years. While significant inverse optimization literature exists for convex…

Optimization and Control · Mathematics 2021-09-02 Merve Bodur , Timothy C. Y. Chan , Ian Yihang Zhu

Cutting planes for mixed-integer linear programs (MILPs) are typically computed in rounds by iteratively solving optimization problems, the so-called separation. Instead, we reframe the problem of finding good cutting planes as a continuous…

Optimization and Control · Mathematics 2023-07-10 Didier Chételat , Andrea Lodi

An algorithm for irreducible decomposition of representations of finite groups over fields of characteristic zero is described. The algorithm uses the fact that the decomposition induces a partition of the invariant inner product into a…

Representation Theory · Mathematics 2019-06-05 Vladimir V Kornyak

It is well-known that by adding integrality constraints to the semidefinite programming (SDP) relaxation of the max-cut problem, the resulting integer semidefinite program is an exact formulation of the problem. In this paper we show…

Optimization and Control · Mathematics 2023-11-09 Frank de Meijer , Renata Sotirov

Substitute valuations (in some contexts called gross substitute valuations) are prominent in combinatorial auction theory. An algorithm is given in this paper for generating a substitute valuation through Monte Carlo simulation. In…

Computer Science and Game Theory · Computer Science 2014-08-15 Bruce Hajek

We apply some recent developments of Baldoni-Beck-Cochet-Vergne on vector partition function, to Kostant's and Steinberg's formulae, for classical Lie algebras $A\_r$, $B\_r$, $C\_r$, $D\_r$. We therefore get efficient {\tt Maple} programs…

Representation Theory · Mathematics 2009-09-29 Charles Cochet

We give a short survey on computational techniques which can be used to solve the representation conversion problem for polyhedra up to symmetries. We in particular discuss decomposition methods, which reduce the problem to a number of…

Metric Geometry · Mathematics 2011-10-20 David Bremner , Mathieu Dutour Sikiric , Achill Schuermann

This paper explores a new class of constrained difference programming problems, where the objective and constraints are formulated as differences of functions, without requiring their convexity. To investigate such problems, novel variants…

Optimization and Control · Mathematics 2026-04-21 Boris S. Mordukhovich , Yixia Song , Shangzhi Zeng , Jin Zhang

We address the problem of complementing higher-order patterns without repetitions of existential variables. Differently from the first-order case, the complement of a pattern cannot, in general, be described by a pattern, or even by a…

Logic in Computer Science · Computer Science 2008-10-22 Alberto Momigliano , Frank Pfenning

In this paper, we present a novel approach to synthesize invariant clusters for polynomial programs. An invariant cluster is a set of program invariants that share a common structure, which could, for example, be used to save the needs for…

Systems and Control · Computer Science 2022-03-16 Qiuye Wang , Lihong Zhi , Naijun Zhan , Bai Xue , Zhi-hong Yang

Bilevel programs model sequential decision interactions between two sets of players and find wide applications in real-world complex systems. In this paper, we consider a bilevel mixed-integer linear program with binary tender, wherein the…

Optimization and Control · Mathematics 2025-09-03 Bo Zhou , Ruiwei Jiang , Siqian Shen

A novel two-phase molecule inference framework, mol-infer, has recently been developed to infer chemical graphs with prescribed abstract structures and desired property values through mixed integer linear programming (MILP) under the…

Quantitative Methods · Quantitative Biology 2026-05-29 Jianshen Zhu , Raveena Rai , Taiyo Sohkawa , Naveed Ahmed Azam , Kazuya Haraguchi , Liang Zhao , Tatsuya Akutsu

We propose a new method for separating valid inequalities for the epigraph of a function of binary variables. The proposed inequalities are disjunctive cuts defined by disjunctive terms obtained by enumerating a subset $I$ of the binary…

Optimization and Control · Mathematics 2022-07-12 Rui Chen , James Luedtke

This paper proposes a method for the automatic creation of variables (in the case of regression) that complement the information contained in the initial input vector. The method works as a pre-processing step in which the continuous values…

Machine Learning · Computer Science 2024-03-14 Colin Troisemaine , Vincent Lemaire