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We investigate the complexity of bilevel combinatorial optimization with uncertainty in the follower's objective, in a robust optimization approach. We show that the robust counterpart of the bilevel problem under interval uncertainty can…

Optimization and Control · Mathematics 2021-08-05 Christoph Buchheim , Dorothee Henke , Felix Hommelsheim

In this work we extend the results of previous derivations of Seiberg-like dualities (level-rank duality) between gauged Wess-Zumino-Witten theories. The arguments in use to identify a potential dual for the supersymmetric WZW theory based…

High Energy Physics - Theory · Physics 2015-12-09 Edwin Ireson

We investigate optimality conditions for optimization problems constrained by a class of variational inequalities of the second kind. Based on a nonsmooth primal-dual reformulation of the governing inequality, the differentiability of the…

Optimization and Control · Mathematics 2014-07-08 Juan-Carlos De Los Reyes , Christian Meyer

Usually, bilevel optimization problems need to be transformed into single-level ones in order to derive optimality conditions and solution algorithms. Among the available approaches, the replacement of the lower-level problem by means of…

Optimization and Control · Mathematics 2025-02-17 Stephan Dempe , Patrick Mehlitz

Construction of tight confidence regions and intervals is central to statistical inference and decision making. This paper develops new theory showing minimum average volume confidence regions for categorical data. More precisely, consider…

Machine Learning · Statistics 2021-02-01 Matthew L. Malloy , Ardhendu Tripathy , Robert D. Nowak

Understanding the generalization properties of heavy-tailed stochastic optimization algorithms has attracted increasing attention over the past years. While illuminating interesting aspects of stochastic optimizers by using heavy-tailed…

Machine Learning · Statistics 2025-06-03 Benjamin Dupuis , Umut Şimşekli

We introduce a robust optimization model consisting in a family of perturbation functions giving rise to certain pairs of dual optimization problems in which the dual variable depends on the uncertainty parameter. The interest of our…

Optimization and Control · Mathematics 2018-03-14 Nguyen Dinh , Miguel A. Goberna , Marco A. López , Michel Volle

The duality map between gauge theories and strings suggests that when the gauge theory is in the weak coupling regime the dual string tension effectively tends to zero, $\alpha' \to \infty$. This observation of Sundborg and Witten initiates…

High Energy Physics - Theory · Physics 2007-05-23 G. Savvidy

A lively ongoing debate is taking place, since the extraordinary emergence of Large Language Models (LLMs) with regards to their capability to understand the world and capture the meaning of the dialogues in which they are involved.…

Computation and Language · Computer Science 2025-05-09 Daniel N. Nissani

We establish two global boundedness results for weak solutions to generalized Schr\"{o}dinger-type double phase problems with variable exponents in $\mathbb{R}^N$ under new critical growth conditions optimally introduced in [26, 32]. More…

Analysis of PDEs · Mathematics 2026-04-23 Hoang Hai Ha , Ky Ho , Bui The Quan , Inbo Sim

Langlands duality is one of the most influential topics in mathematical research. It has many different appearances and influential subtopics. Yet there is a topic that until now seems unrelated to the Langlands program. That is the topic…

Representation Theory · Mathematics 2025-01-22 V. K. Dobrev

The extended $T$-systems are a number of short exact sequences in the category of finite-dimensional modules over the quantum affine algebras of types $A_n^{(1)}$ and $B_n^{(1)}$, introduced by Mukhin and Young as a generalization of the…

Quantum Algebra · Mathematics 2024-05-28 Katsuyuki Naoi

In this paper, we consider the robust linear infinite programming problem $({\rm RLIP}_c) $ defined by \begin{eqnarray*} ({\rm RLIP}_c)\quad &&\inf\; \langle c,x\rangle \textrm{subject to } &&x\in X,\; \langle x^\ast,x \rangle \le r…

Optimization and Control · Mathematics 2019-10-25 Dinh Nguyen , Long Dang Hai

It is common practice in statistical data analysis to perform data-driven variable selection and derive statistical inference from the resulting model. Such inference enjoys none of the guarantees that classical statistical theory provides…

Statistics Theory · Mathematics 2013-06-06 Richard Berk , Lawrence Brown , Andreas Buja , Kai Zhang , Linda Zhao

We associate with each convex optimization problem, posed on some locally convex space, with infinitely many constraints indexed by the set T, and a given non-empty family H of finite subsets of T, a suitable Lagrangian-Haar dual problem.…

Optimization and Control · Mathematics 2021-06-04 Nguyen Dih , Miguel A. Goberna , Marco A. López , Michel Volle

Our interest is whether two binomial parameters differ, which parameter is larger, and by how much. This apparently simple problem was addressed by Fisher in the 1930's, and has been the subject of many review papers since then. Yet there…

Methodology · Statistics 2021-04-20 Michael P. Fay , Sally A. Hunsberger

We establish a super duality as an equivalence between Whittaker module categories over a pair of classical Lie algebra and Lie superalgebra in the infinite-rank limit. Building on this result and utilizing the Losev-Shu-Xiao decomposition,…

Representation Theory · Mathematics 2026-01-08 Shun-Jen Cheng , Weiqiang Wang

Many problems in optimization theory are strongly nonlinear in the traditional sense but possess a hidden linear structure over suitable idempotent semirings. After an overview of `Idempotent Mathematics' with an emphasis on matrix theory,…

Numerical Analysis · Mathematics 2025-10-20 Grigori Litvinov , Andrei Sobolevskii

We extend the notion of self-duality to spaces built from a set of representations of the Lorentz group with bosonic or fermionic behaviour, not having the traditional spin-one upper-bound of super Minkowski space. The generalized…

High Energy Physics - Theory · Physics 2009-10-30 C. Devchand , J. Nuyts

We prove the first generalization bound for large-margin halfspaces that is asymptotically tight in the tradeoff between the margin, the fraction of training points with the given margin, the failure probability and the number of training…

Machine Learning · Computer Science 2025-02-20 Kasper Green Larsen , Natascha Schalburg
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