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In this paper, we present a new method for computing bounded-degree factors of lacunary multivariate polynomials. In particular for polynomials over number fields, we give a new algorithm that takes as input a multivariate polynomial f in…

Symbolic Computation · Computer Science 2016-02-01 Bruno Grenet

We propose an algorithm for solving bound-constrained mathematical programs with complementarity constraints on the variables. Each iteration of the algorithm involves solving a linear program with complementarity constraints in order to…

Optimization and Control · Mathematics 2022-01-14 Christian Kirches , Jeffrey Larson , Sven Leyffer , Paul Manns

We study the problem of minimizing a multivariate polynomial function over the unit hypercube. By representing the polynomial through a hypergraph and exploiting its sparsity structure, we establish a new sufficient condition under which…

Optimization and Control · Mathematics 2026-04-29 Aida Khajavirad

We present a first theoretical analysis of the power of polynomial-time preprocessing for important combinatorial problems from various areas in AI. We consider problems from Constraint Satisfaction, Global Constraints, Satisfiability,…

Artificial Intelligence · Computer Science 2011-08-12 Stefan Szeider

Counting distinct permutations with replacement, especially when involving multiple subwords, is a longstanding challenge in combinatorial analysis, with critical applications in cryptography, bioinformatics, and statistical modeling. This…

Cryptography and Security · Computer Science 2024-11-27 Martin Mathew , Javier Noda

We study here several variants of the covariates fine balance problem where we generalize some of these problems and introduce a number of others. We present here a comprehensive complexity study of the covariates problems providing…

Data Structures and Algorithms · Computer Science 2020-09-18 Dorit S. Hochbaum , Asaf Levin , Xu Rao

We prove lower bounds of order $n\log n$ for both the problem to multiply polynomials of degree $n$, and to divide polynomials with remainder, in the model of bounded coefficient arithmetic circuits over the complex numbers. These lower…

Computational Complexity · Computer Science 2007-05-23 Peter Buergisser , Martin Lotz

Modeling of high order multivariate probability distribution is a difficult problem which occurs in many fields. Copula approach is a good choice for this purpose, but the curse of dimensionality still remains a problem. In this paper we…

Statistics Theory · Mathematics 2010-09-16 Edith Kovacs , Tamas Szantai

Sequences of discrete random variables are studied whose probability generating functions are zero-free in a sector of the complex plane around the positive real axis. Sharp bounds on the cumulants of all orders are stated, leading to…

Probability · Mathematics 2023-12-04 Nils Heerten , Holger Sambale , Christoph Thäle

This paper considers an optimization problem for a dynamical system whose evolution depends on a collection of binary decision variables. We develop scalable approximation algorithms with provable suboptimality bounds to provide…

Optimization and Control · Mathematics 2016-10-31 Insoon Yang , Samuel A. Burden , Ram Rajagopal , S. Shankar Sastry , Claire J. Tomlin

We develop improved rearrangement algorithms to find the dependence structure that minimizes a convex function of the sum of dependent variables with given margins. We propose a new multivariate dependence measure, which can assess the…

Computation · Statistics 2016-07-14 Carole Bernard , Don McLeish

We describe a general technique that yields the first {\em Statistical Query lower bounds} for a range of fundamental high-dimensional learning problems involving Gaussian distributions. Our main results are for the problems of (1) learning…

Machine Learning · Computer Science 2017-05-18 Ilias Diakonikolas , Daniel M. Kane , Alistair Stewart

The study of the fundamental limits of information systems is a central theme in information theory. Both the traditional analytical approach and the recently proposed computational approach have significant limitations, where the former is…

Information Theory · Computer Science 2022-05-04 Wenjing Chen , Chao Tian

We investigate the existence of a fundamental computation-information gap for the problem of clustering a mixture of isotropic Gaussian in the high-dimensional regime, where the ambient dimension $p$ is larger than the number $n$ of points.…

Statistics Theory · Mathematics 2024-02-29 Bertrand Even , Christophe Giraud , Nicolas Verzelen

This paper introduces a novel method for approximating the dynamics of a large autonomous system projected onto a fixed subspace. The core contribution is a novel recursive algorithm to construct an effective time-dependent generator that…

Quantum Physics · Physics 2025-10-24 Tommaso Grigoletto

The works presented in this habilitation concern the algorithmics of polynomials. This is a central topic in computer algebra, with numerous applications both within and outside the field - cryptography, error-correcting codes, etc. For…

Symbolic Computation · Computer Science 2026-03-09 Bruno Grenet

With this paper, we contribute to the growing research area of feature-based analysis of bio-inspired computing. In this research area, problem instances are classified according to different features of the underlying problem in terms of…

Neural and Evolutionary Computing · Computer Science 2016-02-10 Shayan Poursoltan , Frank Neumann

Cardinality estimation and conjunctive query evaluation are two of the most fundamental problems in database query processing. Recent work proposed, studied, and implemented a robust and practical information-theoretic cardinality…

Databases · Computer Science 2025-04-04 Sungjin Im , Benjamin Moseley , Hung Q. Ngo , Kirk Pruhs

We study fundamental block-structured integer programs called tree-fold and multi-stage IPs. Tree-fold IPs admit a constraint matrix with independent blocks linked together by few constraints in a recursive pattern; and transposing their…

Computational Complexity · Computer Science 2024-02-28 Christoph Hunkenschröder , Kim-Manuel Klein , Martin Koutecký , Alexandra Lassota , Asaf Levin

We consider adaptive decision-making problems where an agent optimizes a cumulative performance objective by repeatedly choosing among a finite set of options. Compared to the classical prediction-with-expert-advice set-up, we consider…

Machine Learning · Computer Science 2023-04-10 Michael Muehlebach