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In this self-contained paper, we present a theory of the piecewise linear minimal valid functions for the 1-row Gomory-Johnson infinite group problem. The non-extreme minimal valid functions are those that admit effective perturbations. We…

Optimization and Control · Mathematics 2022-09-08 Robert Hildebrand , Matthias Köppe , Yuan Zhou

The termination problem for affine programs over the integers was left open in\cite{Braverman}. For more that a decade, it has been considered and cited as a challenging open problem. To the best of our knowledge, we present here the most…

Discrete Mathematics · Computer Science 2014-09-19 Rachid Rebiha , Arnaldo Vieira Moura , Nadir Matringe

The Johnson-Lindenstrauss Lemma states that there exist linear maps that project a set of points of a vector space into a space of much lower dimension such that the Euclidean distance between these points is approximately preserved. This…

Optimization and Control · Mathematics 2023-01-18 Pierre-Louis Poirion , Bruno F. Lourenço , Akiko Takeda

We consider the differentiation of the value function for parametric optimization problems. Such problems are ubiquitous in Machine Learning applications such as structured support vector machines, matrix factorization and min-min or…

Optimization and Control · Mathematics 2020-12-29 Sheheryar Mehmood , Peter Ochs

Supervised dimensionality reduction has emerged as an important theme in the last decade. Despite the plethora of models and formulations, there is a lack of a simple model which aims to project the set of patterns into a space defined by…

Machine Learning · Statistics 2016-10-28 Anthony O. Smith , Anand Rangarajan

We consider the nonlinear integer programming problem of minimizing a quadratic function over the integer points in variable dimension satisfying a system of linear inequalities. We show that when the Graver basis of the matrix defining the…

Optimization and Control · Mathematics 2014-05-08 Jon Lee , Shmuel Onn , Lyubov Romanchuk , Robert Weismantel

In this paper, we consider the quadratic programming problems under finitely many convex quadratic constraints in Hilbert spaces. By using the Legendre property of quadratic forms or the compactness of operators in the presentations of…

Optimization and Control · Mathematics 2016-05-03 Vu Van Dong , Nguyen Nang Tam

We show that the set of Lebesgue integrable functions in $[0,1]$ which are nowhere essentially bounded is spaceable, improving a result from [F. J. Garc\'{i}a-Pacheco, M. Mart\'{i}n, and J. B. Seoane-Sep\'ulveda. \textit{Lineability,…

Functional Analysis · Mathematics 2012-05-01 Szymon Glab , Pedro L. Kaufmann , Leonardo Pellegrini

With the increasing interest in applying the methodology of difference-of-convex (dc) optimization to diverse problems in engineering and statistics, this paper establishes the dc property of many well-known functions not previously known…

Optimization and Control · Mathematics 2019-02-20 Maher Nouiehed , Jong-Shi Pang , Meisam Razaviyayn

A famous question of Halmos asks whether every operator on a separable infinite-dimensional Hilbert space is a norm limit of reducible operators. In [30], Voiculescu gave this problem an affirmative answer by his remarkable non-commutative…

Operator Algebras · Mathematics 2025-10-31 Junhao Shen , Rui Shi

Given a cover $\mathcal{B}$ of a quasi-uniform space $Y$ we introduce a concept of lower semicontinuity for multifunctions $F:X\to 2^Y$, called $\mathcal{B}$-lsc. In this way, we get a common description of Vietoris-lsc, Hausdorff-lsc, and…

General Topology · Mathematics 2007-05-23 Andrzej Spakowski

In functional analysis it is well known that every linear functional defined on the dual of a locally convex vector space which is continuous for the weak topology is the evaluation at a uniquely determined point of the given vector space.…

Logic in Computer Science · Computer Science 2017-01-11 Klaus Keimel

This paper is concerned with the directional derivative of the value function for a very general set-constrained optimization problem under perturbation. Under reasonable assumptions, we obtain upper and lower estimates for the upper and…

Optimization and Control · Mathematics 2023-11-08 Kuang Bai , Jane Ye

The functional linear model extends the notion of linear regression to the case where the response and covariates are iid elements of an infinite dimensional Hilbert space. The unknown to be estimated is a Hilbert-Schmidt operator, whose…

Statistics Theory · Mathematics 2016-12-22 Tung Pham , Victor Panaretos

The addition of lower level integrality constraints to a bi-level linear program is known to result in significantly weaker analytical properties. Most notably, the upper level goal function in the optimistic setting lacks lower…

Optimization and Control · Mathematics 2022-12-13 Johanna Burtscheidt , Matthias Claus

This paper is concerned with the question of reconstructing a vector in a finite-dimensional real Hilbert space when only the magnitudes of the coefficients of the vector under a redundant linear map are known. We analyze various Lipschitz…

Functional Analysis · Mathematics 2013-08-23 Radu Balan , Yang Wang

This paper discusses differential stability of convex programming problems in Hausdorff locally convex topological vector spaces. Among other things, we obtain formulas for computing or estimating the subdifferential and the singular…

Optimization and Control · Mathematics 2018-05-08 Duong Thi Viet An , Nguyen Dong Yen

Langrange duality theorems for vector and set optimization problems which are based on an consequent usage of infimum and supremum (in the sense greatest lower and least upper bounds with respect to a partial ordering) have been recently…

Optimization and Control · Mathematics 2014-04-07 Elvira Hernández , Andreas Löhne , Luis Rodríguez-Marín , Christiane Tammer

The completely bounded trace and spectral norms, for finite-dimensional spaces, are known to be efficiently expressible by semidefinite programs (J. Watrous, Theory of Computing 5: 11, 2009). This paper presents two new, and arguably much…

Quantum Physics · Physics 2012-08-03 John Watrous

We present the first optimal rates for infinite-dimensional vector-valued ridge regression on a continuous scale of norms that interpolate between $L_2$ and the hypothesis space, which we consider as a vector-valued reproducing kernel…

Machine Learning · Statistics 2024-08-07 Zhu Li , Dimitri Meunier , Mattes Mollenhauer , Arthur Gretton