Matthew W. Hoffman

30 papers A* 5A 2Misc 1Journal 18Unranked 4

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Knowledge Transfer from Teachers to Learners in Growing-Batch Reinforcement Learning. CoRR Patrick Emedom-Nnamdi, Abram L. Friesen, Bobak Shahriari, Nando de Freitas, Matthew W. Hoffman
2021	J	`jnl`	Launchpad: A Programming Model for Distributed Machine Learning Research. CoRR Fan Yang, Gabriel Barth-Maron, Piotr Stanczyk, Matthew W. Hoffman, Siqi Liu, Manuel Kroiss, Aedan Pope, Alban Rrustemi
2021	J	`jnl`	Regularized Behavior Value Estimation. CoRR Çaglar Gülçehre, Sergio Gómez Colmenarejo, Ziyu Wang, Jakub Sygnowski, Thomas Paine, Konrad Zolna, Yutian Chen, Matthew W. Hoffman, Razvan Pascanu, Nando de Freitas
2019	J	`jnl`	Improving the Gating Mechanism of Recurrent Neural Networks. CoRR Albert Gu, Çaglar Gülçehre, Tom Le Paine, Matthew W. Hoffman, Razvan Pascanu
2019	A	`conf`	Large-Scale Visual Speech Recognition. INTERSPEECH Brendan Shillingford, Yannis M. Assael, Matthew W. Hoffman, Thomas Paine, Cían Hughes, Utsav Prabhu, Hank Liao, Hasim Sak, Kanishka Rao, Lorrayne Bennett, Marie Mulville, Misha Denil, Ben Coppin, Ben Laurie, Andrew W. Senior, Nando de Freitas
2019	J	`jnl`	Modular Meta-Learning with Shrinkage. CoRR Yutian Chen, Abram L. Friesen, Feryal M. P. Behbahani, David Budden, Matthew W. Hoffman, Arnaud Doucet, Nando de Freitas
2018	—	`conf`	Distributed Distributional Deterministic Policy Gradients. ICLR (Poster) Gabriel Barth-Maron, Matthew W. Hoffman, David Budden, Will Dabney, Dan Horgan, Dhruva TB, Alistair Muldal, Nicolas Heess, Timothy P. Lillicrap
2018	J	`jnl`	Distributed Distributional Deterministic Policy Gradients. CoRR Gabriel Barth-Maron, Matthew W. Hoffman, David Budden, Will Dabney, Dan Horgan, Dhruva TB, Alistair Muldal, Nicolas Heess, Timothy P. Lillicrap
2018	J	`jnl`	Large-Scale Visual Speech Recognition. CoRR Brendan Shillingford, Yannis M. Assael, Matthew W. Hoffman, Thomas Paine, Cían Hughes, Utsav Prabhu, Hank Liao, Hasim Sak, Kanishka Rao, Lorrayne Bennett, Marie Mulville, Ben Coppin, Ben Laurie, Andrew W. Senior, Nando de Freitas
2018	J	`jnl`	One-Shot High-Fidelity Imitation: Training Large-Scale Deep Nets with RL. CoRR Tom Le Paine, Sergio Gomez Colmenarejo, Ziyu Wang, Scott E. Reed, Yusuf Aytar, Tobias Pfaff, Matthew W. Hoffman, Gabriel Barth-Maron, Serkan Cabi, David Budden, Nando de Freitas
2017	A*	`conf`	Learned Optimizers that Scale and Generalize. ICML Olga Wichrowska, Niru Maheswaranathan, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Nando de Freitas, Jascha Sohl-Dickstein
2017	J	`jnl`	Learned Optimizers that Scale and Generalize. CoRR Olga Wichrowska, Niru Maheswaranathan, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Nando de Freitas, Jascha Sohl-Dickstein
2017	A*	`conf`	Learning to Learn without Gradient Descent by Gradient Descent. ICML Yutian Chen, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Timothy P. Lillicrap, Matthew M. Botvinick, Nando de Freitas
2017	Misc	`conf`	The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously. CoRL Serkan Cabi, Sergio Gomez Colmenarejo, Matthew W. Hoffman, Misha Denil, Ziyu Wang, Nando de Freitas
2017	J	`jnl`	The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously. CoRR Serkan Cabi, Sergio Gomez Colmenarejo, Matthew W. Hoffman, Misha Denil, Ziyu Wang, Nando de Freitas
2016	J	`jnl`	A General Framework for Constrained Bayesian Optimization using Information-based Search. J. Mach. Learn. Res. José Miguel Hernández-Lobato, Michael A. Gelbart, Ryan P. Adams, Matthew W. Hoffman, Zoubin Ghahramani
2016	J	`jnl`	Learning to Learn for Global Optimization of Black Box Functions. CoRR Yutian Chen, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Timothy P. Lillicrap, Nando de Freitas
2016	—	`conf`	Learning to learn by gradient descent by gradient descent. NIPS Marcin Andrychowicz, Misha Denil, Sergio Gomez Colmenarejo, Matthew W. Hoffman, David Pfau, Tom Schaul, Nando de Freitas
2016	J	`jnl`	Learning to learn by gradient descent by gradient descent. CoRR Marcin Andrychowicz, Misha Denil, Sergio Gomez Colmenarejo, Matthew W. Hoffman, David Pfau, Tom Schaul, Nando de Freitas
2015	A*	`conf`	Predictive Entropy Search for Bayesian Optimization with Unknown Constraints. ICML José Miguel Hernández-Lobato, Michael A. Gelbart, Matthew W. Hoffman, Ryan P. Adams, Zoubin Ghahramani
2014	J	`jnl`	An Entropy Search Portfolio for Bayesian Optimization. CoRR Bobak Shahriari, Ziyu Wang, Matthew W. Hoffman, Alexandre Bouchard-Côté, Nando de Freitas
2014	A	`conf`	On correlation and budget constraints in model-based bandit optimization with application to automatic machine learning. AISTATS Matthew W. Hoffman, Bobak Shahriari, Nando de Freitas
2014	—	`conf`	Predictive Entropy Search for Efficient Global Optimization of Black-box Functions. NIPS José Miguel Hernández-Lobato, Matthew W. Hoffman, Zoubin Ghahramani
2014	J	`jnl`	Predictive Entropy Search for Efficient Global Optimization of Black-box Functions. CoRR José Miguel Hernández-Lobato, Matthew W. Hoffman, Zoubin Ghahramani
2013	J	`jnl`	Best arm identification via Bayesian gap-based exploration CoRR Matthew W. Hoffman, Bobak Shahriari, Nando de Freitas
2011	A*	`conf`	Finite-Sample Analysis of Lasso-TD. ICML Mohammad Ghavamzadeh, Alessandro Lazaric, Rémi Munos, Matthew W. Hoffman
2011	—	`conf`	Regularized Least Squares Temporal Difference Learning with Nested ℓ2 and ℓ1 Penalization. EWRL Matthew W. Hoffman, Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos
2010	J	`jnl`	Portfolio Allocation for Bayesian Optimization CoRR Eric Brochu, Matthew W. Hoffman, Nando de Freitas
2006	J	`jnl`	A probabilistic model of gaze imitation and shared attention. Neural Networks Matthew W. Hoffman, David B. Grimes, Aaron P. Shon, Rajesh P. N. Rao
2005	A*	`conf`	Probabilistic Gaze Imitation and Saliency Learning in a Robotic Head. ICRA Aaron P. Shon, David B. Grimes, Chris L. Baker, Matthew W. Hoffman, Shengli Zhou, Rajesh P. N. Rao