5 papers · 1 filter
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…
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…
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…
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…
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…