3 citations · 3 across the 5 of their papers we have counts for
Showing 2025Show all
2 papers · 1 filter
cs.LG2025
Enabling Pareto-Stationarity Exploration in Multi-Objective Reinforcement Learning: A Multi-Objective Weighted-Chebyshev Actor-Critic Approach
Fnu Hairi, Jiao Yang, Tianchen Zhou +6
In many multi-objective reinforcement learning (MORL) applications, being able to systematically explore the Pareto-stationary solutions under multiple non-convex reward objectives…
cs.LG2025
STIMULUS: Achieving Fast Convergence and Low Sample Complexity in Stochastic Multi-Objective Learning
Zhuqing Liu, Chaosheng Dong, Michinari Momma +5
Recently, multi-objective optimization (MOO) has gained attention for its broad applications in ML, operations research, and engineering. However, MOO algorithm design remains in i…