4 citations · 6 across the 7 of their papers we have counts for
7 papers
Interpretable and Fair Generalized Additive Neural Networks via Multi-objective Learning
Ziming Wang, Changwu Huang, Ke Tang +2
Interpretability and fairness are two of the most emphasized dimensions in trustworthy artificial intelligence (AI). Various explainable AI methods have been introduced to improve…
CASE: Causal Alignment and Structural Enforcement for Improving Chain-of-Thought Faithfulness
Ziming Wang, Yinghua Yao, Changwu Huang +2
Chain-of-thought (CoT) reasoning is widely used to improve both the performance and interpretability of large language models (LLMs), yet the generated reasoning may not faithfully…
Robust Dynamic Material Handling via Adaptive Constrained Evolutionary Reinforcement Learning
Chengpeng Hu, Ziming Wang, Bo Yuan +3
Dynamic material handling (DMH) involves the assignment of dynamically arriving material transporting tasks to suitable vehicles in real time for minimising makespan and tardiness.…
Procedural Fairness and Its Relationship with Distributive Fairness in Machine Learning
Ziming Wang, Changwu Huang, Ke Tang +1
Fairness in machine learning (ML) has garnered significant attention in recent years. While existing research has predominantly focused on the distributive fairness of ML models, t…
Procedural Fairness in Machine Learning
Ziming Wang, Changwu Huang, Ke Tang +1
Fairness in machine learning (ML) has garnered significant attention. However, current research has mainly concentrated on the distributive fairness of ML models, with limited focu…
Constrained Reinforcement Learning for Dynamic Material Handling
Chengpeng Hu, Ziming Wang, Jialin Liu +3
As one of the core parts of flexible manufacturing systems, material handling involves storage and transportation of materials between workstations with automated vehicles. The imp…
An Efficient Multi-Indicator and Many-Objective Optimization Algorithm based on Two-Archive
Ziming Wang, Xin Yao
Indicator-based algorithms are gaining prominence as traditional multi-objective optimization algorithms based on domination and decomposition struggle to solve many-objective opti…