Bobak Shahriari

21 papers A* 4A 2B 1Journal 14

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	BOND: Aligning LLMs with Best-of-N Distillation. ICLR Pier Giuseppe Sessa, Robert Dadashi-Tazehozi, Léonard Hussenot, Johan Ferret, Nino Vieillard, Alexandre Ramé, Bobak Shahriari, Sarah Perrin, Abram L. Friesen, Geoffrey Cideron, Sertan Girgin, Piotr Stanczyk, Andrea Michi, Danila Sinopalnikov, Sabela Ramos Garea, Amélie Héliou, Aliaksei Severyn, Matthew Hoffman, Nikola Momchev, Olivier Bachem
2025	J	`jnl`	Capturing Individual Human Preferences with Reward Features. CoRR André Barreto, Vincent Dumoulin, Yiran Mao, Nicolas Perez Nieves, Bobak Shahriari, Yann N. Dauphin, Doina Precup, Hugo Larochelle
2025	A*	`conf`	Learning from negative feedback, or positive feedback or both. ICLR Abbas Abdolmaleki, Bilal Piot, Bobak Shahriari, Jost Tobias Springenberg, Tim Hertweck, Michael Bloesch, Rishabh Joshi, Thomas Lampe, Junhyuk Oh, Nicolas Heess, Jonas Buchli, Martin A. Riedmiller
2024	J	`jnl`	BOND: Aligning LLMs with Best-of-N Distillation. CoRR Pier Giuseppe Sessa, Robert Dadashi, Léonard Hussenot, Johan Ferret, Nino Vieillard, Alexandre Ramé, Bobak Shahriari, Sarah Perrin, Abe Friesen, Geoffrey Cideron, Sertan Girgin, Piotr Stanczyk, Andrea Michi, Danila Sinopalnikov, Sabela Ramos, Amélie Héliou, Aliaksei Severyn, Matt Hoffman, Nikola Momchev, Olivier Bachem
2024	J	`jnl`	Preference Optimization as Probabilistic Inference. CoRR Abbas Abdolmaleki, Bilal Piot, Bobak Shahriari, Jost Tobias Springenberg, Tim Hertweck, Rishabh Joshi, Junhyuk Oh, Michael Bloesch, Thomas Lampe, Nicolas Heess, Jonas Buchli, Martin A. Riedmiller
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
2022	J	`jnl`	Revisiting Gaussian mixture critics in off-policy reinforcement learning: a sample-based approach. CoRR Bobak Shahriari, Abbas Abdolmaleki, Arunkumar Byravan, Abe Friesen, Siqi Liu, Jost Tobias Springenberg, Nicolas Heess, Matt Hoffman, Martin A. Riedmiller
2021	J	`jnl`	On Multi-objective Policy Optimization as a Tool for Reinforcement Learning. CoRR Abbas Abdolmaleki, Sandy H. Huang, Giulia Vezzani, Bobak Shahriari, Jost Tobias Springenberg, Shruti Mishra, Dhruva TB, Arunkumar Byravan, Konstantinos Bousmalis, András György, Csaba Szepesvári, Raia Hadsell, Nicolas Heess, Martin A. Riedmiller
2020	J	`jnl`	Acme: A Research Framework for Distributed Reinforcement Learning. CoRR Matt Hoffman, Bobak Shahriari, John Aslanides, Gabriel Barth-Maron, Feryal M. P. Behbahani, Tamara Norman, Abbas Abdolmaleki, Albin Cassirer, Fan Yang, Kate Baumli, Sarah Henderson, Alexander Novikov, Sergio Gómez Colmenarejo, Serkan Cabi, Çaglar Gülçehre, Tom Le Paine, Andrew Cowie, Ziyu Wang, Bilal Piot, Nando de Freitas
2020	A*	`conf`	Critic Regularized Regression. NeurIPS Ziyu Wang, Alexander Novikov, Konrad Zolna, Josh Merel, Jost Tobias Springenberg, Scott E. Reed, Bobak Shahriari, Noah Y. Siegel, Çaglar Gülçehre, Nicolas Heess, Nando de Freitas
2020	J	`jnl`	Critic Regularized Regression. CoRR Ziyu Wang, Alexander Novikov, Konrad Zolna, Jost Tobias Springenberg, Scott E. Reed, Bobak Shahriari, Noah Y. Siegel, Josh Merel, Çaglar Gülçehre, Nicolas Heess, Nando de Freitas
2020	A*	`conf`	Making Efficient Use of Demonstrations to Solve Hard Exploration Problems. ICLR Çaglar Gülçehre, Tom Le Paine, Bobak Shahriari, Misha Denil, Matt Hoffman, Hubert Soyer, Richard Tanburn, Steven Kapturowski, Neil C. Rabinowitz, Duncan Williams, Gabriel Barth-Maron, Ziyu Wang, Nando de Freitas, Worlds Team
2019	J	`jnl`	Making Efficient Use of Demonstrations to Solve Hard Exploration Problems. CoRR Tom Le Paine, Çaglar Gülçehre, Bobak Shahriari, Misha Denil, Matt Hoffman, Hubert Soyer, Richard Tanburn, Steven Kapturowski, Neil C. Rabinowitz, Duncan Williams, Gabriel Barth-Maron, Ziyu Wang, Nando de Freitas, Worlds Team
2017	J	`jnl`	A combined finite element and Bayesian optimization framework for shape optimization in spectral geometry. Comput. Math. Appl. Sebastián Domínguez, Nilima Nigam, Bobak Shahriari
2016	J	`jnl`	Taking the Human Out of the Loop: A Review of Bayesian Optimization. Proc. IEEE Bobak Shahriari, Kevin Swersky, Ziyu Wang, Ryan P. Adams, Nando de Freitas
2016	A	`conf`	Unbounded Bayesian Optimization via Regularization. AISTATS Bobak Shahriari, Alexandre Bouchard-Côté, Nando de Freitas
2016	B	`conf`	Which Learning Algorithms Can Generalize Identity-Based Rules to Novel Inputs? CogSci Paul F. Tupper, Bobak Shahriari
2016	J	`jnl`	Which Learning Algorithms Can Generalize Identity-Based Rules to Novel Inputs? CoRR Paul F. Tupper, Bobak Shahriari
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
2013	J	`jnl`	Best arm identification via Bayesian gap-based exploration CoRR Matthew W. Hoffman, Bobak Shahriari, Nando de Freitas