12 citations · 18 across the 11 of their papers we have counts for
5 papers · 1 filter
Tuning-Free Bilevel Optimization: New Algorithms and Convergence Analysis
Yifan Yang, Hao Ban, Minhui Huang +2
Bilevel optimization has recently attracted considerable attention due to its abundant applications in machine learning problems. However, existing methods rely on prior knowledge…
Imperative Learning: A Self-supervised Neuro-Symbolic Learning Framework for Robot Autonomy
Chen Wang, Kaiyi Ji, Junyi Geng +16
Data-driven methods such as reinforcement and imitation learning have achieved remarkable success in robot autonomy. However, their data-centric nature still hinders them from gene…
MGDA Converges under Generalized Smoothness, Provably
Qi Zhang, Peiyao Xiao, Shaofeng Zou +1
Multi-objective optimization (MOO) is receiving more attention in various fields such as multi-task learning. Recent works provide some effective algorithms with theoretical analys…
Theoretical Study of Conflict-Avoidant Multi-Objective Reinforcement Learning
Yudan Wang, Peiyao Xiao, Hao Ban +2
Multi-task reinforcement learning (MTRL) has shown great promise in many real-world applications. Existing MTRL algorithms often aim to learn a policy that optimizes individual obj…
Fair Resource Allocation in Multi-Task Learning
Hao Ban, Kaiyi Ji
By jointly learning multiple tasks, multi-task learning (MTL) can leverage the shared knowledge across tasks, resulting in improved data efficiency and generalization performance.…