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20172026
most citedSolving Nonsmooth Nonconvex Compound Stochastic Programs with Applications to Risk Measure Minimization

2 citations · 4 across the 7 of their papers we have counts for

collaborators

7 papers

math.OC2026

A New Perspective on Clustering: A Mixed-norm Model and its Solution by Progressive Integer Programming

Junyi Liu, Yulin Peng, Yao Xie +2

Extending the classical -means and -medians models, this paper introduces an mixed-norm clustering model where the centroid updates and cluster assignments are u…

math.OC2026

Online Optimization of Difference-of-Convex Compositions with Smooth Mappings

Jingwei Ji, Jong-Shi Pang, Renyuan Xu

We study online optimization for a broad class of structured non-convex non-smooth problems where each loss is a composition of a difference-of-convex function with a smooth mappin…

math.OC2026

Solving Constrained Affine Heaviside Composite Optimization Problems by a Progressive IP Approach

Ke Zheng, Junyi Liu, Yurui Wang +1

This paper discusses the computational resolution and presents numerical results for solving affine combinations of Heaviside composite optimization problems (abbreviated as A-HSCO…

math.OC2026

Offline Policy Learning with Weight Clipping and Heaviside Composite Optimization

Jingren Liu, Hanzhang Qin, Junyi Liu +2

Offline policy learning aims to use historical data to learn an optimal personalized decision rule. In the standard estimate-then-optimize framework, reweighting-based methods (e.g…

math.OC2024

Classification and Treatment Learning with Constraints via Composite Heaviside Optimization: a Progressive MIP Method

Yue Fang, Junyi Liu, Jong-Shi Pang

This paper proposes a Heaviside composite optimization approach and presents a progressive (mixed) integer programming (PIP) method for solving multi-class classification and multi…

math.OC2020★ 2 cited

Solving Nonsmooth Nonconvex Compound Stochastic Programs with Applications to Risk Measure Minimization

Junyi Liu, Ying Cui, Jong-Shi Pang

This paper studies a structured compound stochastic program (SP) involving multiple expectations coupled by nonconvex and nonsmooth functions. We present a successive convex-progra…

math.OC2017★ 2 cited

On the Pervasiveness of Difference-Convexity in Optimization and Statistics

Maher Nouiehed, Jong-Shi Pang, Meisam Razaviyayn

With the increasing interest in applying the methodology of difference-of-convex (dc) optimization to diverse problems in engineering and statistics, this paper establishes the dc…