期刊： MATHEMATICAL PROGRAMMING, ; ()
In the Euclidean setting the proximal gradient method and its accelerated variants are a class of efficient algorithms for optimization problems with ......
期刊： MATHEMATICAL PROGRAMMING, ; ()
In this paper, a novel stochastic extra-step quasi-Newton method is developed to solve a class of nonsmooth nonconvex composite optimization problems.......
期刊： MATHEMATICAL PROGRAMMING, ; ()
Choice of a risk measure for quantifying risk of an investment portfolio depends on the decision maker's risk preference. In this paper, we consider t......
期刊： MATHEMATICAL PROGRAMMING, 2021; 185 (1-2)
We consider a class of mathematical programs with complementarity constraints (MPCC) where the objective function involves a non-Lipschitz sparsity-in......
期刊： MATHEMATICAL PROGRAMMING, 2021; 185 (1-2)
Monotonicity and convex analysis arise naturally in the framework of multi-marginal optimal transport theory. However, a comprehensive multi-marginal ......
期刊： MATHEMATICAL PROGRAMMING, 2021; 185 (1-2)
In this paper, we show that for a class of linearly constrained convex composite optimization problems, an (inexact) symmetric Gauss-Seidel based majo......
期刊： MATHEMATICAL PROGRAMMING, 2021; 185 (1-2)
The notion of perfect equilibrium was formulated by Selten (Int J Game Theory 4(1):25-55, 1975) as a strict refinement of Nash equilibrium. For an ext......
期刊： MATHEMATICAL PROGRAMMING, 2020; 181 (2)
We study risk sharing problems with quantile-based risk measures and heterogeneous beliefs, motivated by the use of internal models in finance and ins......
期刊： MATHEMATICAL PROGRAMMING, 2020; 182 (1-2)
Composite minimization involves a collection of smooth functions which are aggregated in a nonsmooth manner. In the convex setting, we design an algor......
期刊： MATHEMATICAL PROGRAMMING, 2020; 184 (1-2)
In this paper we study nonconvex and nonsmooth multi-block optimization over Euclidean embedded (smooth) Riemannian submanifolds with coupled linear c......
期刊： MATHEMATICAL PROGRAMMING, 2020; 184 (1-2)
Beck and Teboulle's FISTA method for finding a minimizer of the sum of two convex functions, one of which has a Lipschitz continuous gradient whereas ......
期刊： MATHEMATICAL PROGRAMMING, 2020; 184 (1-2)
We consider fractional online covering problems withlq-norm objectives as well as its dual packing problems. The problem of interest is of the formmin......
期刊： MATHEMATICAL PROGRAMMING, 2020; 181 (2)
This paper begins with a study on the dual representations of risk and regret measures and their impact on modeling multistage decision making under u......
期刊： MATHEMATICAL PROGRAMMING, 2020; 180 (1-2)
This paper reveals that a common and central role, played in many error bound (EB) conditions and a variety of gradient-type methods, is a residual me......
期刊： MATHEMATICAL PROGRAMMING, 2020; 180 (1-2)
Conditional value at risk (CVaR) has been widely studied as a risk measure. In this paper we add to this work by focusing on the choice of confidence ......
