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The cross-entropy method (CE) developed by R. Rubinstein is an elegant practical principle for simulating rare events. The method approximates the probability of the rare event by means of a family of probabilistic models. The method has…

Optimization and Control · Mathematics 2007-06-13 Frederic Dambreville

A lexicographic maximum of a set $X \subseteq \mathbb{R}^n$ is a vector in $X$ whose smallest component is as large as possible, and subject to that requirement, whose second smallest component is as large as possible, and so on for the…

Optimization and Control · Mathematics 2024-05-03 Jacob Abernethy , Robert E. Schapire , Umar Syed

Submodularity is a fundamental phenomenon in combinatorial optimization. Submodular functions occur in a variety of combinatorial settings such as coverage problems, cut problems, welfare maximization, and many more. Therefore, a lot of…

Data Structures and Algorithms · Computer Science 2011-11-08 Shaddin Dughmi

We introduce the homogeneous and piecewise multilinear extensions and the eigenvalue problem for locally Lipschitz function pairs, in order to develop a systematic framework for relating discrete and continuous min-max problems. This also…

Combinatorics · Mathematics 2021-11-25 Jürgen Jost , Dong Zhang

Maximum-entropy ensembles are key primitives in statistical mechanics from which thermodynamic properties can be derived. Over the decades, several approaches have been put forward in order to justify from minimal assumptions the use of…

Quantum Physics · Physics 2018-03-13 Paul Boes , Henrik Wilming , Jens Eisert , Rodrigo Gallego

It is proved the existence of entire solutions of the Laplace's and minimal hypersurface's PDEs on a Hadamard manifold $M$ under certain curvature conditions by investigating the asymptotic Dirichlet's problems for these PDEs. In the…

Differential Geometry · Mathematics 2012-02-29 Jaime Ripoll , Miriam Telichevesky

In [1] we consider an optimal control problem subject to a semilinear elliptic PDE together with its variational discretization, where we provide a condition which allows to decide whether a solution of the necessary first order conditions…

Optimization and Control · Mathematics 2017-05-04 Ahmad Ahmad Ali , Klaus Deckelnick , Michael Hinze

We study the sample complexity of the best-case Empirical Risk Minimizer in the setting of stochastic convex optimization. We show that there exists an instance in which the sample size is linear in the dimension, learning is possible, but…

Machine Learning · Computer Science 2026-02-10 Tal Burla , Roi Livni

Local reasoning about programs that combine aliasing and mutable state is a longstanding challenge. Existing approaches -- ownership systems, linear and affine types, uniqueness types, and lexical effect tracking -- impose global…

Programming Languages · Computer Science 2025-09-01 Haotian Deng , Siyuan He , Songlin Jia , Yuyan Bao , Tiark Rompf

Extremal Optimization, a recently introduced meta-heuristic for hard optimization problems, is analyzed on a simple model of jamming. The model is motivated first by the problem of finding lowest energy configurations for a disordered spin…

Statistical Mechanics · Physics 2018-07-06 S. Boettcher , M. Grigni

We explore a new general-purpose heuristic for finding high-quality solutions to hard optimization problems. The method, called extremal optimization, is inspired by self-organized criticality, a concept introduced to describe emergent…

Statistical Mechanics · Physics 2009-10-31 S. Boettcher , A. G. Percus

The convergence of expectation-maximization (EM)-based algorithms typically requires continuity of the likelihood function with respect to all the unknown parameters (optimization variables). The requirement is not met when parameters…

Signal Processing · Electrical Eng. & Systems 2024-04-18 Geethu Joseph

We prove some regularity results for a connected set S in the planar domain O, which minimizes the compliance of its complement O\S, plus its length. This problem, interpreted as to find the best location for attaching a membrane subject to…

Optimization and Control · Mathematics 2016-04-18 Antonin Chambolle , Jimmy Lamboley , Antoine Lemenant , Eugene Stepanov

Cyber-physical systems are conducting increasingly complex tasks, which are often modeled using formal languages such as temporal logic. The system's ability to perform the required tasks can be curtailed by malicious adversaries that mount…

Systems and Control · Computer Science 2019-07-25 Luyao Niu , Jie Fu , Andrew Clark

In this paper, we study the regularity assumptions commonly adopted in bilevel optimization with constrained lower-level problems, including the linear independence constraint qualification, the strict complementary slackness condition, and…

Optimization and Control · Mathematics 2026-05-15 Xiaotian Jiang , Chang He , Mingyi Hong , Shuzhong Zhang

Model Multiplicity (MM) arises when multiple, equally performing machine learning models can be trained to solve the same prediction task. Recent studies show that models obtained under MM may produce inconsistent predictions for the same…

Machine Learning · Computer Science 2024-01-04 Junqi Jiang , Antonio Rago , Francesco Leofante , Francesca Toni

We establish a general condition on the cost function to obtain uniqueness and Monge solutions in the multi-marginal optimal transport problem, under the assumption that a given collection of the marginals are absolutely continuous with…

Optimization and Control · Mathematics 2022-02-15 Brendan Pass , Adolfo Vargas-Jiménez

Assume $D$ is a finite set and $R$ is a finite set of functions from $D$ to the natural numbers. An instance of the minimum $R$-cost homomorphism problem ($MinHom_R$) is a set of variables $V$ subject to specified constraints together with…

Computational Complexity · Computer Science 2012-10-09 Rustem Takhanov

The CP-violating phenomenology of the MSSM with Minimal Flavor Violation (MFV) in the lepton sector is revisited. To this end, the most general parametrizations of the slepton soft-breaking terms are constructed assuming a seesaw mechanism…

High Energy Physics - Phenomenology · Physics 2014-11-18 Lorenzo Mercolli , Christopher Smith

We provide an optimization-based argument for the monotonicity of the multiplicative algorithm (MA) for a class of optimal experimental design problems considered in Yu (2010). Our proof avoids introducing auxiliary variables (or problems)…

Optimization and Control · Mathematics 2025-08-12 Renbo Zhao