Accurate, Explainable, and Private Models: Providing Recourse While Minimizing Training Data Leakage

no code implementations • 8 Aug 2023 • Catherine Huang, Chelse Swoopes, Christina Xiao, Jiaqi Ma, Himabindu Lakkaraju

We present two novel methods to generate differentially private recourse: Differentially Private Model (DPM) and Laplace Recourse (LR).

Offline Meta-Reinforcement Learning with Online Self-Supervision

1 code implementation • 8 Jul 2021 • Vitchyr H. Pong, Ashvin Nair, Laura Smith, Catherine Huang, Sergey Levine

If we can meta-train on offline data, then we can reuse the same static dataset, labeled once with rewards for different tasks, to meta-train policies that adapt to a variety of new tasks at meta-test time.

Meta Reinforcement Learning Offline RL +2