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Michael Zhang
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Year
Lookahead optimizer: k steps forward, 1 step back
M Zhang, J Lucas, GE Hinton, J Ba
Advances in Neural Information Processing Systems, 9597-9608, 2019
4572019
Reverse curriculum generation for reinforcement learning
C Florensa, D Held, M Wulfmeier, M Zhang, P Abbeel
Conference on Robot Learning (CoRL), 2017
3302017
Benchmarks for Deep Off-Policy Evaluation
J Fu, M Norouzi, O Nachum, G Tucker, Z Wang, A Novikov, M Yang, ...
arXiv preprint arXiv:2103.16596, 2021
292021
Probabilistically safe policy transfer
D Held, Z McCarthy, M Zhang, F Shentu, P Abbeel
2017 IEEE International Conference on Robotics and Automation (ICRA), 5798-5805, 2017
252017
Lookahead Optimizer: K steps forward, 1 step back. arXiv 2019
MR Zhang, J Lucas, G Hinton, J Ba
arXiv preprint arXiv:1907.08610, 0
11
Analyzing Monotonic Linear Interpolation in Neural Network Loss Landscapes
J Lucas, J Bae, MR Zhang, S Fort, R Zemel, R Grosse
arXiv preprint arXiv:2104.11044, 2021
102021
Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization
MR Zhang, TL Paine, O Nachum, C Paduraru, G Tucker, Z Wang, ...
arXiv preprint arXiv:2104.13877, 2021
92021
On Monotonic Linear Interpolation of Neural Network Parameters
JR Lucas, J Bae, MR Zhang, S Fort, R Zemel, RB Grosse
International Conference on Machine Learning, 7168-7179, 2021
32021
Learning domain invariant representations in goal-conditioned block mdps
B Han, C Zheng, H Chan, K Paster, M Zhang, J Ba
Advances in Neural Information Processing Systems 34, 764-776, 2021
22021
Objective Social Choice: Using Auxiliary Information to Improve Voting Outcomes
S Pitis, MR Zhang
International Conference on Autonomous Agents and Multi-Agent Systems 2020, 2020
2020
Robustness to Adversarial Gradients: A Glimpse Into the Loss Landscape of Contrastive Pre-training
P Fradkin, L Atanackovic, MR Zhang
First Workshop on Pre-training: Perspectives, Pitfalls, and Paths Forward at …, 0
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Articles 1–11