1 citations · 1 across the 3 of their papers we have counts for
4 papers
Learning Choice Model Trees for Feature-Based Multi-Product Pricing: Exact Optimization and Field Evidence
Jiajie Zhang, Yanqiu Ruan, Xiao Jin +1
Feature-based multi-product pricing uses customer characteristics to identify demand heterogeneity and tailor prices across products. Choice model trees segment customers through i…
Optimizer as Detector: Stochastic Gradient Descent for Latent Mixture Models
Ye Shi, Xiao Jin, Chung-Piaw Teo
Pooling latent subpopulations can obscure relationships and yield misleading regression conclusions, including Simpson's paradox (SP). We propose a detector based on the steady-sta…
Large-Scale Optimization Model Auto-Formulation: Harnessing LLM Flexibility via Structured Workflow
Kuo Liang, Yuhang Lu, Jianming Mao +7
Large-scale optimization is a key backbone of modern business decision-making. However, building these models is often labor-intensive and time-consuming. We address this by propos…
Enhancing binary classification: A new stacking method via leveraging computational geometry
Wei Wu, Liang Tang, Zhongjie Zhao +1
Stacking, a potent ensemble learning method, leverages a meta-model to harness the strengths of multiple base models, thereby enhancing prediction accuracy. Traditional stacking te…