Michael Luo | DeepAI

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∙ 01/05/2022

Balsa: Learning a Query Optimizer Without Expert Demonstrations

Query optimizers are a performance-critical component in every database ...

13 Zongheng Yang, et al. ∙

∙ 12/07/2021

MESA: Offline Meta-RL for Safe Adaptation and Fault Tolerance

Safe exploration is critical for using reinforcement learning (RL) in ri...

19 Michael Luo, et al. ∙

∙ 07/22/2021

Accelerating Quadratic Optimization with Reinforcement Learning

First-order methods for quadratic optimization such as OSQP are widely u...

10 Jeffrey Ichnowski, et al. ∙

∙ 03/31/2021

LazyDAgger: Reducing Context Switching in Interactive Imitation Learning

Corrective interventions while a robot is learning to automate a task pr...

6 Ryan Hoque, et al. ∙

∙ 11/27/2020

Connecting Context-specific Adaptation in Humans to Meta-learning

Cognitive control, the ability of a system to adapt to the demands of a ...

0 Rachit Dubey, et al. ∙

∙ 11/25/2020

Distributed Reinforcement Learning is a Dataflow Problem

Researchers and practitioners in the field of reinforcement learning (RL...

20 Eric Liang, et al. ∙

∙ 10/29/2020

Recovery RL: Safe Reinforcement Learning with Learned Recovery Zones

Safety remains a central obstacle preventing widespread use of RL in the...

15 Brijen Thananjeyan, et al. ∙

∙ 11/30/2019

IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks

The practical usage of reinforcement learning agents is often bottleneck...

5 Michael Luo, et al. ∙

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