Ikuti
Matthew W. Hoffman
Matthew W. Hoffman
Google DeepMind
Email yang diverifikasi di google.com - Beranda
Judul
Dikutip oleh
Dikutip oleh
Tahun
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
25282016
Predictive entropy search for efficient global optimization of black-box functions
JM Hernández-Lobato, MW Hoffman, Z Ghahramani
Advances in neural information processing systems 27, 2014
8652014
Distributed distributional deterministic policy gradients
G Barth-Maron, MW Hoffman, D Budden, W Dabney, D Horgan, D Tb, ...
arXiv preprint arXiv:1804.08617, 2018
7052018
Belief tracking and action selection in spoken dialog systems
R Gupta, D Ramachandran, A Raux, N Mehta, S Krawczyk, M Hoffman
US Patent 8,676,583, 2014
4202014
Portfolio Allocation for Bayesian Optimization.
MW Hoffman, E Brochu, N de Freitas
UAI, 327-336, 2011
4002011
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
3632017
Learned optimizers that scale and generalize
O Wichrowska, N Maheswaranathan, MW Hoffman, SG Colmenarejo, ...
International conference on machine learning, 3751-3760, 2017
3372017
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
2752020
Large-scale visual speech recognition
B Shillingford, Y Assael, MW Hoffman, T Paine, C Hughes, U Prabhu, ...
arXiv preprint arXiv:1807.05162, 2018
2132018
A general framework for constrained Bayesian optimization using information-based search
JM Hernández-Lobato, MA Gelbart, RP Adams, MW Hoffman, ...
Journal of Machine Learning Research 17 (160), 1-53, 2016
2032016
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
2022020
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
1972015
On correlation and budget constraints in model-based bandit optimization with application to automatic machine learning
MW Hoffman, B Shahriari, N de Freitas
Proceedings of the Seventeenth International Conference on Artificial …, 2014
1822014
A probabilistic model of gaze imitation and shared attention
MW Hoffman, DB Grimes, AP Shon, RPN Rao
Neural Networks 19 (3), 299-310, 2006
1032006
An entropy search portfolio for Bayesian optimization
B Shahriari, Z Wang, MW Hoffman, A Bouchard-Côté, N de Freitas
arXiv preprint arXiv:1406.4625, 2014
862014
Finite-sample analysis of Lasso-TD
M Ghavamzadeh, A Lazaric, R Munos, MW Hoffman
International Conference on Machine Learning, 2011
592011
Regularized Least Squares Temporal Difference Learning with Nested ℓ2 and ℓ1 Penalization
MW Hoffman, A Lazaric, M Ghavamzadeh, R Munos
European Workshop on Reinforcement Learning, 102-114, 2011
582011
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
502020
Output-space predictive entropy search for flexible global optimization
MW Hoffman, Z Ghahramani
NIPS workshop on Bayesian Optimization, 1-5, 2015
452015
Bayesian policy learning with trans-dimensional MCMC
M Hoffman, A Doucet, N Freitas, A Jasra
Advances in neural information processing systems 20, 2007
432007
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