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Evan Z Liu

2 accepted papers

2021

Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices

ICML 2021spotlight

The goal of meta-reinforcement learning (meta-RL) is to build agents that can quickly learn new tasks by leveraging prior experience on related tasks. Learning a new task often requires both exploring to gather task-relevant information and exploiting this information to solve the task. In principle…

2021

Just Train Twice: Improving Group Robustness without Training Group Information

ICML 2021oral

Standard training via empirical risk minimization (ERM) can produce models that achieve low error on average but high error on minority groups, especially in the presence of spurious correlations between the input and label. Prior approaches to this problem, like group distributionally robust optimi…