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Matthew W. Hoffman
Matthew W. Hoffman
Google DeepMind
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Title
Cited by
Year
Distributional reinforcement learning for continuous control tasks
D Budden, MW Hoffman, G Barth-Maron
US Patent 11,948,085, 2024
2024
Training machine learning models by determining update rules using neural networks
MMR Denil, T Schaul, M Andrychowicz, JFG de Freitas, SG Colmenarejo, ...
US Patent App. 18/180,754, 2023
2023
Knowledge Transfer from Teachers to Learners in Growing-Batch Reinforcement Learning
P Emedom-Nnamdi, AL Friesen, B Shahriari, N de Freitas, MW Hoffman
arXiv preprint arXiv:2305.03870, 2023
2023
Training machine learning models by determining update rules using recurrent neural networks
MMR Denil, T Schaul, M Andrychowicz, JFG De Freitas, SG Colmenarejo, ...
US Patent 11,615,310, 2023
2023
Distributional reinforcement learning for continuous control tasks
D Budden, MW Hoffman, G Barth-Maron
US Patent 11,481,629, 2022
92022
Launchpad: A programming model for distributed machine learning research
F Yang, G Barth-Maron, P Stańczyk, M Hoffman, S Liu, M Kroiss, A Pope, ...
arXiv preprint arXiv:2106.04516, 2021
212021
Regularized behavior value estimation
C Gulcehre, SG Colmenarejo, Z Wang, J Sygnowski, T Paine, K Zolna, ...
arXiv preprint arXiv:2103.09575, 2021
332021
Acme: A research framework for distributed reinforcement learning
MW Hoffman, B Shahriari, J Aslanides, G Barth-Maron, N Momchev, ...
arXiv preprint arXiv:2006.00979, 2020
2392020
Modular meta-learning with shrinkage
Y Chen, AL Friesen, F Behbahani, A Doucet, D Budden, M Hoffman, ...
Advances in Neural Information Processing Systems 33, 2858-2869, 2020
442020
Addressing Extrapolation Error in Deep Offline Reinforcement Learning
C Gulcehre, SG Colmenarejo, J Sygnowski, T Paine, K Zolna, Y Chen, ...
32020
Rl unplugged: A suite of benchmarks for offline reinforcement learning
C Gulcehre, Z Wang, A Novikov, T Paine, S Gómez, K Zolna, R Agarwal, ...
Advances in Neural Information Processing Systems 33, 7248-7259, 2020
1672020
One-shot high-fidelity imitation: Training large-scale deep nets with rl
TL Paine, SG Colmenarejo, Z Wang, S Reed, Y Aytar, T Pfaff, ...
arXiv preprint arXiv:1810.05017, 2018
272018
Large-scale visual speech recognition
B Shillingford, Y Assael, MW Hoffman, T Paine, C Hughes, U Prabhu, ...
arXiv preprint arXiv:1807.05162, 2018
1912018
Distributed distributional deterministic policy gradients
G Barth-Maron, MW Hoffman, D Budden, W Dabney, D Horgan, D Tb, ...
arXiv preprint arXiv:1804.08617, 2018
6262018
The intentional unintentional agent: Learning to solve many continuous control tasks simultaneously
S Cabi, SG Colmenarejo, MW Hoffman, M Denil, Z Wang, N Freitas
Conference on Robot Learning, 207-216, 2017
392017
Learned optimizers that scale and generalize
O Wichrowska, N Maheswaranathan, MW Hoffman, SG Colmenarejo, ...
International conference on machine learning, 3751-3760, 2017
3092017
Learning to learn without gradient descent by gradient descent
Y Chen, MW Hoffman, SG Colmenarejo, M Denil, TP Lillicrap, M Botvinick, ...
International Conference on Machine Learning, 748-756, 2017
335*2017
Learning to learn by gradient descent by gradient descent
M Andrychowicz, M Denil, S Gomez, MW Hoffman, D Pfau, T Schaul, ...
Advances in neural information processing systems 29, 2016
22942016
A general framework for constrained Bayesian optimization using information-based search
JM Hern, MA Gelbart, RP Adams, MW Hoffman, Z Ghahramani
Journal of Machine Learning Research 17 (160), 1-53, 2016
1842016
Predictive entropy search for Bayesian optimization with unknown constraints
JM Hernández-Lobato, M Gelbart, M Hoffman, R Adams, Z Ghahramani
International conference on machine learning, 1699-1707, 2015
1792015
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Articles 1–20