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We develop a divergence-minimization (DM) framework for robust and efficient inference in latent-mixture models. By optimizing a residual-adjusted divergence, the DM approach recovers EM as a special case and yields robust alternatives…

Statistics Theory · Mathematics 2025-11-25 Lei Li , Anand N. Vidyashankar

This paper discusses a general and useful stability principle which, roughly speaking, says that given a uniformly continuous function defined on an arbitrary metric space, if the function is bounded on the constraint set and we slightly…

Optimization and Control · Mathematics 2020-09-04 Daniel Reem , Simeon Reich , Alvaro De Pierro

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 ask what happens when the index set carries modal structure, with possibilities organized into a Kripke frame. We define modal exchangeability as invariance under accessibility-preserving automorphisms that fix a designated base world,…

Logic · Mathematics 2026-04-16 Daniel Zantedeschi

Non-local correlations between a fully characterised quantum system and an untrusted black box device are described by an assemblage of conditional quantum states. These assemblages form a convex set, whose extremal points are relevant in…

Quantum Physics · Physics 2022-09-14 Thomas Cope , Tobias J. Osborne

This paper develops a geometric framework for the stability analysis of differential inclusions governed by maximally monotone operators. A key structural decomposition expresses the operator as the sum of a convexified limit mapping and a…

Optimization and Control · Mathematics 2025-07-18 Hassan Saoud , Michel Théra , Minh N. Dao

The problem of approximating the discrete spectra of families of self-adjoint operators that are merely strongly continuous is addressed. It is well-known that the spectrum need not vary continuously (as a set) under strong perturbations.…

Spectral Theory · Mathematics 2016-03-08 Jonathan Ben-Artzi , Thomas Holding

Necessary conditions for existence of normal extremals in optimal control of systems subject to nonholonomic constraints are derived as solutions of a constrained second order variational problems. In this work, a geometric interpretation…

Optimization and Control · Mathematics 2017-02-08 Leonardo Colombo

We consider a Hilbert space that is a product of a finite number of Hilbert spaces and operators that are represented by "componental operators" acting on the Hilbert spaces that form the product space. We attribute operatorial properties…

Functional Analysis · Mathematics 2021-11-30 Andrzej Cegielski , Yair Censor

Optimal control problems with symmetries often admit a non stationary turnpike property called trim turnpike, which characterizes the convergence of optimal solutions to certain symmetry induced trajectories called trim primitives. In this…

Optimization and Control · Mathematics 2026-04-27 Sofya Maslovskaya , Sina Ober-Blöbaum , Boris Wembe

We study the statistics of the maximum and minimum of a set of $N$ random variables whose dynamical and statistical properties fall within the scope of infinite ergodic theory. These non-stationary yet recurrent systems are described, in…

Statistical Mechanics · Physics 2026-03-09 Talia Baravi , Eli Barkai

A geometric setup for constrained variational calculus is presented. The analysis deals with the study of the extremals of an action functional defined on piecewise differentiable curves, subject to differentiable, non-holonomic…

Mathematical Physics · Physics 2015-05-08 Enrico Massa , Danilo Bruno , Gianvittorio Luria , Enrico Pagani

In this paper we develop new extremal principles in variational analysis that deal with finite and infinite systems of convex and nonconvex sets. The results obtained, unified under the name of tangential extremal principles, combine primal…

Optimization and Control · Mathematics 2011-01-24 Boris S. Mordukhovich , Hung M. Phan

This paper establishes comprehensive stability results for quasi-variational inequalities (QVIs) under monotone perturbations of the governing operator. We prove strong convergence of both minimal and maximal solutions when sequences of…

Functional Analysis · Mathematics 2025-12-16 M. H. M. Rashid

Skew-symmetric families of distributions such as the skew-normal and skew-$t$ represent supersets of the normal and $t$ distributions, and they exhibit richer classes of extremal behaviour. By defining a non-stationary skew-normal process,…

Methodology · Statistics 2016-04-19 Boris Beranger , Simone A. Padoan , Scott A. Sisson

We consider a nonlinear system, affine with respect to an unbounded control $u$ which is allowed to range in a closed cone. To this system we associate a Bolza type minimum problem, with a Lagrangian having sublinear growth with respect to…

Optimization and Control · Mathematics 2019-07-11 M. Soledad Aronna , Monica Motta , Franco Rampazzo

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

In this paper, we study a maximization and a minimization problem associated with a Poisson boundary value problem. Optimal solutions in a set of rearrangements of a given function define stationary and stable flows of an ideal fluid in two…

Optimization and Control · Mathematics 2016-01-07 Seyyed Abbas Mohammadi

We study discrete time linear constrained switching systems with additive disturbances, in which the switching may be on the system matrices, the disturbance sets, the state constraint sets or a combination of the above. In our general…

Systems and Control · Computer Science 2017-02-03 Nikolaos Athanasopoulos , Konstantinos Smpoukis , Raphael M. Jungers

Robust and distributionally robust optimization are modeling paradigms for decision-making under uncertainty where the uncertain parameters are only known to reside in an uncertainty set or are governed by any probability distribution from…

Optimization and Control · Mathematics 2023-07-21 Jianzhe Zhen , Daniel Kuhn , Wolfram Wiesemann