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cs.LG2026
CoAction: Cross-task Correlation-aware Pareto Set Learning
Xinyue Chen, Yingxuan Liang, Yiqin Huang +3
Pareto set learning (PSL) is an emerging paradigm in multi-objective optimization that trains neural networks to map preference vectors to Pareto optimal solutions. However, existi…
cs.LG2026
ELSA: Efficient LLM-Centric Split Aggregation for Privacy-Aware Hierarchical Federated Learning over the Network Edge
Xiaohong Yang, Tong Xie, Minghui Liwang +6
Training large language models (LLMs) in resource-constrained edge networks poses fundamental challenges in computation, communication, data heterogeneity, and privacy. To address…
cs.LG2024
Collaborative Pareto Set Learning in Multiple Multi-Objective Optimization Problems
Chikai Shang, Rongguang Ye, Jiaqi Jiang +1
Pareto Set Learning (PSL) is an emerging research area in multi-objective optimization, focusing on training neural networks to learn the mapping from preference vectors to Pareto…