A Novel Scalable Framework For Constructing Dynamic Multi-objective Optimization Problems. - Qingshan Tan; Changhe Li; Hai Xia 001; Sanyou Zeng; Shengxiang Yang (CEC, 2021)

A Reinforcement-Learning-Based Evolutionary Algorithm Using Solution Space Clustering For Multimodal Optimization Problems. - Hai Xia 001; Changhe Li; Sanyou Zeng; Qingshan Tan; Junchen Wang; Shengxiang Yang (CEC, 2021)

Learning to Search Promising Regions by a Monte-Carlo Tree Model. - Hai Xia 001; Changhe Li; Sanyou Zeng; Qingshan Tan; Junchen Wang; Shengxiang Yang (CEC, 2022)

SAT-Based Tree Decomposition with Iterative Cascading Policy Selection. - Hai Xia 001; Stefan Szeider (AAAI, 2024)

The Power of Collaboration: Learning Large Bayesian Networks at Scale. - Vaidyanathan Peruvemba Ramaswamy; Stefan Szeider; Hai Xia 001 (ICTAI, 2024)

collab-bn-slim. - Vaidyanathan Peruvemba Ramaswamy; Stefan Szeider; Hai Xia 001 (Zenodo, 2024)

Learning to search promising regions by space partitioning for evolutionary methods. - Hai Xia 001; Changhe Li; Qingshan Tan; Sanyou Zeng; Shengxiang Yang (Swarm Evol. Comput., 2024)

Uncovering and Verifying Optimal Community Structure in Complex Networks: A MaxSAT Approach. - Carlos Ansótegui; Vaidyanathan Peruvemba Ramaswamy; Stefan Szeider; Hai Xia 001 (ICCS (2), 2025)

Supplementary material for Smart Cubing for Graph Search: A Comparative Study. - Tomás Peitl; Stefan Szeider; Markus Kirchweger; Hai Xia 001 (Zenodo, 2025)

Smart Cubing for Graph Search: A Comparative Study. - Markus Kirchweger; Hai Xia 001; Tomás Peitl; Stefan Szeider (CoRR, 2025)