66 citations · 115 across the 9 of their papers we have counts for
9 papers
Safe Reinforcement Learning by Imagining the Near Future
Garrett Thomas, Yuping Luo, Tengyu Ma
Safe reinforcement learning is a promising path toward applying reinforcement learning algorithms to real-world problems, where suboptimal behaviors may lead to actual negative con…
Learning Barrier Certificates: Towards Safe Reinforcement Learning with Zero Training-time Violations
Yuping Luo, Tengyu Ma
Training-time safety violations have been a major concern when we deploy reinforcement learning algorithms in the real world. This paper explores the possibility of safe RL algorit…
Towards Learning to Play Piano with Dexterous Hands and Touch
Huazhe Xu, Yuping Luo, Shaoxiong Wang +2
The virtuoso plays the piano with passion, poetry and extraordinary technical ability. As Liszt said (a virtuoso)must call up scent and blossom, and breathe the breath of life. The…
Towards Resolving the Implicit Bias of Gradient Descent for Matrix Factorization: Greedy Low-Rank Learning
Zhiyuan Li, Yuping Luo, Kaifeng Lyu
Matrix factorization is a simple and natural test-bed to investigate the implicit regularization of gradient descent. Gunasekar et al. (2017) conjectured that Gradient Flow with in…
Provable Representation Learning for Imitation Learning via Bi-level Optimization
Sanjeev Arora, Simon S. Du, Sham Kakade +2
A common strategy in modern learning systems is to learn a representation that is useful for many tasks, a.k.a. representation learning. We study this strategy in the imitation lea…
Learning Self-Correctable Policies and Value Functions from Demonstrations with Negative Sampling
Yuping Luo, Huazhe Xu, Tengyu Ma
Imitation learning, followed by reinforcement learning algorithms, is a promising paradigm to solve complex control tasks sample-efficiently. However, learning from demonstrations…
Implicit Regularization in Deep Matrix Factorization
Sanjeev Arora, Nadav Cohen, Wei Hu +1
Efforts to understand the generalization mystery in deep learning have led to the belief that gradient-based optimization induces a form of implicit regularization, a bias towards…
An online sequence-to-sequence model for noisy speech recognition
Chung-Cheng Chiu, Dieterich Lawson, Yuping Luo +4
Generative models have long been the dominant approach for speech recognition. The success of these models however relies on the use of sophisticated recipes and complicated machin…
Learning Online Alignments with Continuous Rewards Policy Gradient
Yuping Luo, Chung-Cheng Chiu, Navdeep Jaitly +1
Sequence-to-sequence models with soft attention had significant success in machine translation, speech recognition, and question answering. Though capable and easy to use, they req…