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cs.LG2023
Multi-objective Reinforcement Learning with Nonlinear Preferences: Provable Approximation for Maximizing Expected Scalarized Return
Nianli Peng, Muhang Tian, Brandon Fain
We study multi-objective reinforcement learning with nonlinear preferences over trajectories. That is, we maximize the expected value of a nonlinear function over accumulated rewar…
cs.LG2019★ 42 cited
Proportionally Fair Clustering
Xingyu Chen, Brandon Fain, Liang Lyu +1
We extend the fair machine learning literature by considering the problem of proportional centroid clustering in a metric context. For clustering points with centers, we de…