351 citations · 738 across the 22 of their papers we have counts for
23 papers
The Minimization of Piecewise Functions: Pseudo Stationarity
Ying Cui, Junyi Liu, Jong-Shi Pang
There are many significant applied contexts that require the solution of discontinuous optimization problems in finite dimensions. Yet these problems are very difficult, both compu…
Nonconvex and Nonsmooth Approaches for Affine Chance-Constrained Stochastic Programs
Ying Cui, Junyi Liu, Jong-Shi Pang
Chance-constrained programs (CCPs) constitute a difficult class of stochastic programs due to its possible nondifferentiability and nonconvexity even with simple linear random func…
Some Strongly Polynomially Solvable Convex Quadratic Programs with Bounded Variables
Jong-Shi Pang, Shaoning Han
This paper begins with a class of convex quadratic programs (QPs) with bounded variables solvable by the parametric principal pivoting algorithm with strongly po…
Statistical Analysis of Stationary Solutions of Coupled Nonconvex Nonsmooth Empirical Risk Minimization
Zhengling Qi, Ying Cui, Yufeng Liu +1
This paper has two main goals: (a) establish several statistical properties---consistency, asymptotic distributions, and convergence rates---of stationary solutions and values of a…
Estimation of Individualized Decision Rules Based on an Optimized Covariate-Dependent Equivalent of Random Outcomes
Zhengling Qi, Ying Cui, Yufeng Liu +1
Recent exploration of optimal individualized decision rules (IDRs) for patients in precision medicine has attracted a lot of attention due to the heterogeneous responses of patient…
Clustering by Orthogonal NMF Model and Non-Convex Penalty Optimization
Shuai Wang, Tsung-Hui Chang, Ying Cui +1
The non-negative matrix factorization (NMF) model with an additional orthogonality constraint on one of the factor matrices, called the orthogonal NMF (ONMF), has been found a prom…
On Robustness of Individualized Decision Rules
Zhengling Qi, Jong-Shi Pang, Yufeng Liu
With the emergence of precision medicine, estimating optimal individualized decision rules (IDRs) has attracted tremendous attention in many scientific areas. Most existing literat…
A Unifying Framework of High-Dimensional Sparse Estimation with Difference-of-Convex (DC) Regularizations
Shanshan Cao, Xiaoming Huo, Jong-Shi Pang
Under the linear regression framework, we study the variable selection problem when the underlying model is assumed to have a small number of nonzero coefficients (i.e., the underl…
Exact Penalization of Generalized Nash Equilibrium Problems
Qin Ba, Jong-Shi Pang
This paper presents an exact penalization theory of the generalized Nash equilibrium problem (GNEP) that has its origin from the renowned Arrow-Debreu general economic equilibrium…
Composite Difference-Max Programs for Modern Statistical Estimation Problems
Ying Cui, Jong-Shi Pang, Bodhisattva Sen
Many modern statistical estimation problems are defined by three major components: a statistical model that postulates the dependence of an output variable on the input features; a…
On the Finite Number of Directional Stationary Values of Piecewise Programs
Ying Cui, Jong-Shi Pang
Extending a fundamental result for (indefinite) quadratic programs, this paper shows that certain non-convex piecewise programs have only a finite number of directional stationary…
Solving Linear Programs with Complementarity Constraints using Branch-and-Cut
Bin Yu, John E. Mitchell, Jong-Shi Pang
A linear program with linear complementarity constraints (LPCC) requires the minimization of a linear objective over a set of linear constraints together with additional linear com…
A Study of Piecewise Linear-Quadratic Programs
Ying Cui, Tsung-Hui Chang, Mingyi Hong +1
Motivated by a growing list of nontraditional statistical estimation problems of the piecewise kind, this paper provides a survey of known results supplemented with new results for…
On Synchronous, Asynchronous, and Randomized Best-Response schemes for computing equilibria in Stochastic Nash games
Jinlong Lei, Uday V. Shanbhag, Jong-Shi Pang +1
This work considers a stochastic Nash game in which each player solves a parameterized stochastic optimization problem. In deterministic regimes, best-response schemes have been sh…
A Unified Algorithmic Framework for Block-Structured Optimization Involving Big Data
Mingyi Hong, Meisam Razaviyayn, Zhi-Quan Luo +1
This article presents a powerful algorithmic framework for big data optimization, called the Block Successive Upper bound Minimization (BSUM). The BSUM includes as special cases ma…
Computing B-Stationary Points of Nonsmooth DC Programs
Jong-Shi Pang, Meisam Razaviyayn, Alberth Alvarado
Motivated by a class of applied problems arising from physical layer based security in a digital communication system, in particular, by a secrecy sum-rate maximization problem, th…
Parallel Successive Convex Approximation for Nonsmooth Nonconvex Optimization
Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo +1
Consider the problem of minimizing the sum of a smooth (possibly non-convex) and a convex (possibly nonsmooth) function involving a large number of variables. A popular approach to…
A New Distributed DC-Programming Method and its Applications
Alberth Alvarado, Gesualdo Scutari, Jong-Shi Pang
We propose a novel decomposition framework for the distributed optimization of Difference Convex (DC)-type nonseparable sum-utility functions subject to coupling convex constraints…
Decomposition by Partial Linearization: Parallel Optimization of Multi-Agent Systems
Gesualdo Scutari, Francisco Facchinei, Peiran Song +2
We propose a novel decomposition framework for the distributed optimization of general nonconvex sum-utility functions arising naturally in the system design of wireless multiuser…
Joint Sensing and Power Allocation in Nonconvex Cognitive Radio Games: Nash Equilibria and Distributed Algorithms
Gesualdo Scutari, Jong-Shi Pang
In this paper, we propose a novel class of Nash problems for Cognitive Radio (CR) networks, modeled as Gaussian frequency-selective interference channels, wherein each secondary us…
Joint Sensing and Power Allocation in Nonconvex Cognitive Radio Games: Quasi-Nash Equilibria
Jong-Shi Pang, Gesualdo Scutari
In this paper, we propose a novel class of Nash problems for Cognitive Radio (CR) networks composed of multiple primary users (PUs) and secondary users (SUs) wherein each SU (playe…
Real and Complex Monotone Communication Games
Gesualdo Scutari, Francisco Facchinei, Jong-Shi Pang +1
Noncooperative game-theoretic tools have been increasingly used to study many important resource allocation problems in communications, networking, smart grids, and portfolio optim…
On the Global Minimization of the Value-at-Risk
Jong-Shi Pang, Sven Leyffer
In this paper, we consider the nonconvex minimization problem of the value-at-risk (VaR) that arises from financial risk analysis. By considering this problem as a special linear p…