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Related papers: Two-sided linear chance constraints and extensions

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In this paper, we study the linear complementarity problems on extended second order cones. We convert a linear complementarity problem on an extended second order cone into a mixed complementarity problem on the non-negative orthant. We…

Optimization and Control · Mathematics 2018-01-22 S. Z. Németh , L. Xiao

In this paper we develop tools for studying limit theorems by means of convexity. We establish bounds for the discrepancy in total variation between probability measures $\mu$ and $\nu$ such that $\nu$ is log-concave with respect to $\mu$.…

Probability · Mathematics 2022-10-24 Arturo Jaramillo , James Melbourne

Motivated by applications requiring sparse or nonnegative controls, we investigate reachability properties of linear infinite-dimensional control problems under conic constraints. Relaxing the problem to convex constraints if the initial…

Optimization and Control · Mathematics 2024-05-14 Camille Pouchol , Emmanuel Trélat , Christophe Zhang

We study two-stage adjustable robust linear programming in which the right-hand sides are uncertain and belong to a convex, compact uncertainty set. This problem is NP-hard, and the affine policy is a popular, tractable approximation. We…

Optimization and Control · Mathematics 2017-05-23 Guanglin Xu , Samuel Burer

We consider minimization of a smooth nonconvex function with inexact oracle access to gradient and Hessian (without assuming access to the function value) to achieve approximate second-order optimality. A novel feature of our method is that…

Optimization and Control · Mathematics 2024-03-27 Shuyao Li , Stephen J. Wright

We study system design problems stated as parameterized stochastic programs with a chance-constraint set. We adopt a Bayesian approach that requires the computation of a posterior predictive integral which is usually intractable. In…

Machine Learning · Statistics 2020-01-07 Prateek Jaiswal , Harsha Honnappa , Vinayak A. Rao

We consider the problem of approximating the solution of variational problems subject to the constraint that the admissible functions must be convex. This problem is at the interface between convex analysis, convex optimization, variational…

Numerical Analysis · Mathematics 2015-03-19 Adam M. Oberman

We obtain new concavity results, up to a suitable transformation, for a class of quasi-linear equations in a convex domain involving the $p$-Laplace operator and a general nonlinearity satisfying concavity type assumptions. This provides an…

Analysis of PDEs · Mathematics 2022-02-01 William Borrelli , Sunra Mosconi , Marco Squassina

This paper develops a characterisation of when solutions of forced second order linear differential equations converge to the zero solution of the asymptotically stable and unforced second order equation, or when the solution is bounded,…

Classical Analysis and ODEs · Mathematics 2026-03-27 John A. D. Appleby , Subham Pal

While convergence of polynomial chaos approximation for linear equations is relatively well understood, a lot less is known for non-linear equations. The paper investigates this convergence for a particular equation with quadratic…

Numerical Analysis · Mathematics 2021-07-27 S. V. Lototsky , R. Mikulevicius , B. L. Rozovsky

All discretized numerical models contain modelling errors - this reality is amplified when reduced-order models are used. The ability to accurately approximate modelling errors informs statistics on model confidence and improves…

Computational Physics · Physics 2021-03-17 Danny Smyl , Tyler N. Tallman , Jonathan A. Black , Andreas Hauptmann , Dong Liu

In this thesis, we present results related to complementarity problems. We study the linear complementarity problems on extended second order cones. We convert a linear complementarity problem on an extended second order cone into a mixed…

Optimization and Control · Mathematics 2021-08-18 Lianghai Xiao

The paper concerns the second-order generalized differentiation theory of variational analysis and new applications of this theory to some problems of constrained optimization in finitedimensional spaces. The main attention is paid to the…

Optimization and Control · Mathematics 2011-10-21 B. S. Mordukhovich , R. T. Rockafellar

A covariant quantization method for physical systems with reducible constraints is presented.

High Energy Physics - Theory · Physics 2007-05-23 J. Stephany , A. Restuccia

In structured prediction problems where we have indirect supervision of the output, maximum marginal likelihood faces two computational obstacles: non-convexity of the objective and intractability of even a single gradient computation. In…

Machine Learning · Statistics 2016-08-11 Aditi Raghunathan , Roy Frostig , John Duchi , Percy Liang

We prove a general lemma for deriving contraction rates for linear inverse problems with non parametric nonconjugate priors. We then apply it to get contraction rates for both mildly and severely ill posed linear inverse problems with…

Statistics Theory · Mathematics 2017-02-21 Madhuresh

This paper studies two-stage distributionally robust conic linear programming under constraint uncertainty over type-1 Wasserstein balls. We present optimality conditions for the dual of the worst-case expectation problem, which…

Optimization and Control · Mathematics 2024-02-06 Geunyeong Byeon , Kaiwen Fang , Kibaek Kim

This paper tackles the problem of the existence of solutions for recursive systems of Horn clauses with second-order variables interpreted as integer relations, and harnessed by quantifier-free difference bounds arithmetic. We start by…

Formal Languages and Automata Theory · Computer Science 2016-02-16 Radu Iosif

A second-order regularity theory is developed for solutions to a class of quasilinear elliptic equations in divergence form, including the $p$-Laplace equation, with merely square-integrable right-hand side. Our results amount to the…

Analysis of PDEs · Mathematics 2018-05-23 Andrea Cianchi , Vladimir Maz'ya

In this paper, we propose the uncertain volatility models with stochastic bounds. Like the regular uncertain volatility models, we know only that the true model lies in a family of progressively measurable and bounded processes, but instead…

Mathematical Finance · Quantitative Finance 2017-02-17 Jean-Pierre Fouque , Ning Ning
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