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We investigate existence of dual optimizers in one-dimensional martingale optimal transport problems. While [BNT16] established such existence for weak (quasi-sure) duality, [BHP13] showed existence for the natural stronger pointwise…

Probability · Mathematics 2017-05-12 Mathias Beiglboeck , Tongseok Lim , Jan Obłój

Dual first-order methods are powerful techniques for large-scale convex optimization. Although an extensive research effort has been devoted to studying their convergence properties, explicit convergence rates for the primal iterates have…

Optimization and Control · Mathematics 2015-02-24 Jie Lu , Mikael Johansson

We formulate a refined theory of linear systems, using the methods of a previous paper, "A Theory of Branches for Algebraic Curves", and use it to give a geometric interpretation of the genus of an algebraic curve. Using principles of…

Algebraic Geometry · Mathematics 2010-03-31 Tristram de Piro

This paper studies how to train machine-learning models that directly approximate the optimal solutions of constrained optimization problems. This is an empirical risk minimization under constraints, which is challenging as training must…

Machine Learning · Computer Science 2022-11-24 Seonho Park , Pascal Van Hentenryck

We extend the methods and results of [arXiv 1603.04896] to the setting of multinomial distributions satisfying certain properties. These include all the multinomial distributions arising from the direct proof of the Central Limit Theorem…

Probability · Mathematics 2016-06-07 Vladimir Dobric , Patricia Garmirian , Lee J. Stanley

In this note we prove that the factorization theorem for dominated polynomials previously proved by the authors is equivalent to an alternative factorization scheme that uses classical linear techniques and a linearization process. However,…

Functional Analysis · Mathematics 2008-12-09 Geraldo Botelho , Daniel Pellegrino , Pilar Rueda

We provide three new proofs of the strong concavity of the dual function of some convex optimization problems. For problems with nonlinear constraints, we show that the the assumption of strong convexity of the objective cannot be weakened…

Optimization and Control · Mathematics 2021-05-04 Vincent Guigues

We describe a method to discretize optimization problems arising in the regularization of linear inverse problem having compact forward operator defined on 3-D valed measures, compactly supported on a fixed set. The criterion is a quadratic…

Optimization and Control · Mathematics 2025-05-05 L Baratchart , D P Hardin , C Villalobos-Guillén

In this paper, we show that the derivability problem for the primal propositional logic remains solvable in polynomial time upon adding a certain form of the principle of equivalent form substitution; and that, upon adding another form of…

Logic · Mathematics 2020-12-01 Inga Lev

The domain of online algorithms with predictions has been extensively studied for different applications such as scheduling, caching (paging), clustering, ski rental, etc. Recently, Bamas et al., aiming for an unified method, have provided…

Data Structures and Algorithms · Computer Science 2021-10-04 Nguyen Kim Thang , Christoph Durr

The work studies the problem of decentralized constrained POMDPs in a team-setting where multiple nonstrategic agents have asymmetric information. Using an extension of Sion's Minimax theorem for functions with positive infinity and results…

Optimization and Control · Mathematics 2025-04-29 Nouman Khan , Vijay Subramanian

We propose and study a novel stochastic inertial primal-dual approach to solve composite optimization problems. These latter problems arise naturally when learning with penalized regularization schemes. Our analysis provide convergence…

Optimization and Control · Mathematics 2015-07-06 Lorenzo Rosasco , Silvia Villa , Bang Cong Vu

In this paper we design a new primal-dual algorithm for the classic discrete optimization problem of maximizing a monotone submodular function subject to a cardinality constraint achieving the optimal approximation of $(1-1/e)$. This…

Data Structures and Algorithms · Computer Science 2023-11-15 Deeparnab Chakrabarty , Luc Cote

In this paper, we exploit linear programming duality in the online setting (i.e., where input arrives on the fly) from the unique perspective of designing lower bounds on the competitive ratio. In particular, we provide a general technique…

Data Structures and Algorithms · Computer Science 2016-04-07 Yossi Azar , Ilan Reuven Cohen , Alan Roytman

We consider min-max optimization problems for polynomial functions, where a multivariate polynomial is maximized with respect to a subset of variables, and the resulting maximal value is minimized with respect to the remaining variables.…

Optimization and Control · Mathematics 2023-06-27 Francis Bach

In the mid-eighties Tardos proposed a strongly polynomial algorithm for solving linear programming problems for which the size of the coefficient matrix is polynomially bounded by the dimension. Combining Orlin's primal-based modification…

Optimization and Control · Mathematics 2014-09-09 Shinji Mizuno , Noriyoshi Sukegawa , Antoine Deza

Trialitarian automorphisms are related to automorphisms of order 3 of the Dynkin diagram of type D4. Octic etale algebras with trivial discriminant, containing quartic subalgebras, are classified by Galois cohomology with value in the Weyl…

Rings and Algebras · Mathematics 2010-01-27 Max-Albert Knus , Jean-Pierre Tignol

It has been shown that many first-order methods satisfy the perturbed Fenchel duality inequality, which yields a unified derivation of convergence. More first-order methods are discussed in this paper, e.g., dual averaging and bundle…

Optimization and Control · Mathematics 2024-12-04 Tiantian Zhao

Based on the needs of convergence proofs of preconditioned proximal point methods, we introduce notions of partial strong submonotonicity and partial (metric) subregularity of set-valued maps. We study relationships between these two…

Optimization and Control · Mathematics 2020-03-02 Tuomo Valkonen

We consider the triality fusion category discovered in the $c = 1$ KT theory \cite{Thorngren:2021yso}. We analyze this fusion category using the tools from the group theoretical fusion category and describe how to compute the simple lines,…

High Energy Physics - Theory · Physics 2023-02-23 Da-Chuan Lu , Zhengdi Sun