Search Results for author: Zhao Mandi

Found 3 papers, 0 papers with code

On the Effectiveness of Fine-tuning Versus Meta-reinforcement Learning

no code implementations7 Jun 2022 Zhao Mandi, Pieter Abbeel, Stephen James

From these findings, we advocate for evaluating future meta-RL methods on more challenging tasks and including multi-task pretraining with fine-tuning as a simple, yet strong baseline.

Meta-Learning Meta Reinforcement Learning +2

Towards More Generalizable One-shot Visual Imitation Learning

no code implementations26 Oct 2021 Zhao Mandi, Fangchen Liu, Kimin Lee, Pieter Abbeel

We then study the multi-task setting, where multi-task training is followed by (i) one-shot imitation on variations within the training tasks, (ii) one-shot imitation on new tasks, and (iii) fine-tuning on new tasks.

Contrastive Learning Imitation Learning +1

DCUR: Data Curriculum for Teaching via Samples with Reinforcement Learning

no code implementations15 Sep 2021 Daniel Seita, Abhinav Gopal, Zhao Mandi, John Canny

Then, students learn by running either offline RL or by using teacher data in combination with a small amount of self-generated data.

Offline RL reinforcement-learning

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