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Deep models, while being extremely versatile and accurate, are vulnerable to adversarial attacks: slight perturbations that are imperceptible to humans can completely flip the prediction of deep models. Many attack and defense mechanisms…

Machine Learning · Computer Science 2019-07-30 Kaiwen Wu , Yaoliang Yu

We study the problem of bounding path-dependent expectations (within any finite time horizon $d$) over the class of discrete-time martingales whose marginal distributions lie within a prescribed tolerance of a given collection of benchmark…

Probability · Mathematics 2021-12-01 Zhengqing Zhou , Jose Blanchet , Peter W. Glynn

We consider the minimization over probability measures of the expected value of a random variable, regularized by relative entropy with respect to a given probability distribution. In the general setting we provide a complete…

Probability · Mathematics 2020-09-29 Joris Bierkens , Hilbert J. Kappen

In this paper we derive an integral (with respect to time) representation of the relative entropy (or Kullback-Leibler Divergence) between measures mu and P on the space of continuous functions from time 0 to T. The underlying measure P is…

Probability · Mathematics 2014-04-21 James MacLaurin , Olivier Faugeras

In this paper we apply the entropy principle to the relativistic version of the differential equations describing a standard fluid flow, that is, the equations for mass, momentum, and a system for the energy matrix. These are the second…

Mathematical Physics · Physics 2018-02-22 Hans Wilhelm Alt

The martingale expansion provides a refined approximation to the marginal distributions of martingales beyond the normal approximation implied by the martingale central limit theorem. We develop a martingale expansion framework specifically…

Probability · Mathematics 2026-02-06 Masaaki Fukasawa

There is a natural connection between the class of diffusions, and a certain class of solutions to the Skorokhod Embedding Problem (SEP). We show that the important concept of minimality in the SEP leads to the new and useful concept of a…

Probability · Mathematics 2014-02-14 Alexander M. G. Cox , Martin Klimmek

Entropic Optimal Transport (EOT), also referred to as the Schr\"odinger problem, seeks to find a random processes with prescribed initial/final marginals and with minimal relative entropy with respect to a reference measure. The relative…

Optimization and Control · Mathematics 2024-12-17 Jean-David Benamou , Guillaume Chazareix , Marc Hoffmann , Grégoire Loeper , François-Xavier Vialard

In this article we study and classify optimal martingales in the dual formulation of optimal stopping problems. In this respect we distinguish between weakly optimal and surely optimal martingales. It is shown that the family of weakly…

Probability · Mathematics 2021-02-03 Denis Belomestny , John Schoenmakers

Exploiting a fluid dynamic formulation for which a probabilistic counterpart might not be available, we extend the theory of Schroedinger bridges to the case of inertial particles with losses and general, possibly singular diffusion…

Mathematical Physics · Physics 2014-10-08 Yongxin Chen , Tryphon T. Georgiou , Michele Pavon

We consider an optimal transport problem with backward martingale constraint. The objective function is given by the scalar product of a pseudo-Euclidean space $S$. We show that the supremums over maps and plans coincide, provided that the…

Probability · Mathematics 2024-05-30 Dmitry Kramkov , Mihai Sîrbu

When deploying artificial agents in real-world environments where they interact with humans, it is crucial that their behavior is aligned with the values, social norms or other requirements of that environment. However, many environments…

Machine Learning · Computer Science 2023-05-05 Mattijs Baert , Pietro Mazzaglia , Sam Leroux , Pieter Simoens

Following [21, 23], the present work investigates a new relative entropy-regularized algorithm for solving the optimal transport on a graph problem within the randomized shortest paths formalism. More precisely, a unit flow is injected into…

Machine Learning · Computer Science 2021-09-21 Sylvain Courtain , Guillaume Guex , Ilkka Kivimaki , Marco Saerens

We study the interaction between a network designer and an adversary over a dynamical network. The network consists of nodes performing continuous-time distributed averaging. The adversary strategically disconnects a set of links to prevent…

Systems and Control · Computer Science 2015-02-23 Ali Khanafer , Tamer Başar

Within a contest there is some probability M_i(t) that contestant i will be the winner, given information available at time t, and M_i(t) must be a martingale in t. Assume continuous paths, to capture the idea that relevant information is…

Probability · Mathematics 2012-11-12 David Aldous , Mykhaylo Shkolnikov

A novel approach is proposed to establish a sharp upper bound on the expected supremum of a separable martingale random field, serving as an alternative to classical universal chaining-based methods. The proposed approach begins by deriving…

Probability · Mathematics 2026-04-07 Yoichi Nishiyama

In this paper, we introduce weak optimal entropy transport problems that cover both optimal entropy transport problems and weak optimal transport problems introduced by Liero, Mielke, and Savar\'{e} [27]; and Gozlan, Roberto, Samson and…

Functional Analysis · Mathematics 2025-04-15 Nhan-Phu Chung , Thanh-Son Trinh

In this article we study an optimal stopping/optimal control problem which models the decision facing a risk-averse agent over when to sell an asset. The market is incomplete so that the asset exposure cannot be hedged. In addition to the…

Portfolio Management · Quantitative Finance 2008-12-10 Vicky Henderson , David Hobson

We develop a martingale approximation framework yielding quantitative maximal large deviations estimates for invertible dynamical systems. From suitable decay of correlations, we deduce these estimates and, as an application, we obtain…

Dynamical Systems · Mathematics 2026-05-08 José F. Alves , João S. Matias , Ian Melbourne

There has been interest in finding a general variational principle for non-equilibrium statistical mechanics. We give evidence that Maximum Caliber (Max Cal) is such a principle. Max Cal, a variant of Maximum Entropy, predicts dynamical…

Statistical Mechanics · Physics 2015-09-02 Michael J. Hazoglou , Valentin Walther , Purushottam D. Dixit , Ken A. Dill