Zhaohan Guo

According to our database, Zhaohan Guo authored at least 24 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning.

Khimya Khetarpal, Zhaohan Daniel Guo, Bernardo Ávila Pires, Yunhao Tang, Clare Lyle, Mark Rowland, Nicolas Heess, Diana Borsa, Arthur Guez, Will Dabney

CoRR, 2024

Understanding the performance gap between online and offline alignment algorithms.

Yunhao Tang, Zhaohan Daniel Guo, Zeyu Zheng, Daniele Calandriello, Yuan Cao, Eugene Tarassov, Rémi Munos, Bernardo Ávila Pires, Michal Valko, Yong Cheng, Will Dabney

CoRR, 2024

Generalized Preference Optimization: A Unified Approach to Offline Alignment.

Yunhao Tang, Zhaohan Daniel Guo, Zeyu Zheng, Daniele Calandriello, Rémi Munos, Mark Rowland, Pierre Harvey Richemond, Michal Valko, Bernardo Ávila Pires, Bilal Piot

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Nash Learning from Human Feedback.

Rémi Munos, Michal Valko, Daniele Calandriello, Mohammad Gheshlaghi Azar, Mark Rowland, Zhaohan Daniel Guo, Yunhao Tang, Matthieu Geist, Thomas Mesnard, Côme Fiegel, Andrea Michi, Marco Selvi, Sertan Girgin, Nikola Momchev, Olivier Bachem, Daniel J. Mankowitz, Doina Precup, Bilal Piot

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Human Alignment of Large Language Models through Online Preference Optimisation.

Daniele Calandriello, Zhaohan Daniel Guo, Rémi Munos, Mark Rowland, Yunhao Tang, Bernardo Ávila Pires, Pierre Harvey Richemond, Charline Le Lan, Michal Valko, Tianqi Liu, Rishabh Joshi, Zeyu Zheng, Bilal Piot

Proceedings of the Forty-first International Conference on Machine Learning, 2024

A General Theoretical Paradigm to Understand Learning from Human Preferences.

Mohammad Gheshlaghi Azar, Zhaohan Daniel Guo, Bilal Piot, Rémi Munos, Mark Rowland, Michal Valko, Daniele Calandriello

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Nash Learning from Human Feedback.

Rémi Munos, Michal Valko, Daniele Calandriello, Mohammad Gheshlaghi Azar, Mark Rowland, Zhaohan Daniel Guo, Yunhao Tang, Matthieu Geist, Thomas Mesnard, Andrea Michi, Marco Selvi, Sertan Girgin, Nikola Momchev, Olivier Bachem, Daniel J. Mankowitz, Doina Precup, Bilal Piot

CoRR, 2023

Understanding Self-Predictive Learning for Reinforcement Learning.

Yunhao Tang, Zhaohan Daniel Guo, Pierre Harvey Richemond, Bernardo Ávila Pires, Yash Chandak, Rémi Munos, Mark Rowland, Mohammad Gheshlaghi Azar, Charline Le Lan, Clare Lyle, András György, Shantanu Thakoor, Will Dabney, Bilal Piot, Daniele Calandriello, Michal Valko

Proceedings of the International Conference on Machine Learning, 2023

Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition.

Yash Chandak, Shantanu Thakoor, Zhaohan Daniel Guo, Yunhao Tang, Rémi Munos, Will Dabney, Diana L. Borsa

Proceedings of the International Conference on Machine Learning, 2023

2022

BYOL-Explore: Exploration by Bootstrapped Prediction.

Zhaohan Guo, Shantanu Thakoor, Miruna Pislar, Bernardo Ávila Pires, Florent Altché, Corentin Tallec, Alaa Saade, Daniele Calandriello, Jean-Bastien Grill, Yunhao Tang, Michal Valko, Rémi Munos, Mohammad Gheshlaghi Azar, Bilal Piot

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Geometric Entropic Exploration.

Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Alaa Saade, Shantanu Thakoor, Bilal Piot, Bernardo Ávila Pires, Michal Valko, Thomas Mesnard, Tor Lattimore, Rémi Munos

CoRR, 2021

2020

Bootstrap Your Own Latent - A New Approach to Self-Supervised Learning.

Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre H. Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Ávila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, Rémi Munos, Michal Valko

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning.

Zhaohan Daniel Guo, Bernardo Ávila Pires, Bilal Piot, Jean-Bastien Grill, Florent Altché, Rémi Munos, Mohammad Gheshlaghi Azar

Proceedings of the 37th International Conference on Machine Learning, 2020

Agent57: Outperforming the Atari Human Benchmark.

Adrià Puigdomènech Badia, Bilal Piot, Steven Kapturowski, Pablo Sprechmann, Alex Vitvitskyi, Zhaohan Daniel Guo, Charles Blundell

Proceedings of the 37th International Conference on Machine Learning, 2020

Never Give Up: Learning Directed Exploration Strategies.

Adrià Puigdomènech Badia, Pablo Sprechmann, Alex Vitvitskyi, Zhaohan Daniel Guo, Bilal Piot, Steven Kapturowski, Olivier Tieleman, Martín Arjovsky, Alexander Pritzel, Andrew Bolt, Charles Blundell

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Directed Exploration for Reinforcement Learning.

Zhaohan Daniel Guo, Emma Brunskill

CoRR, 2019

2018

Neural Predictive Belief Representations.

Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Bernardo A. Pires, Toby Pohlen, Rémi Munos

CoRR, 2018

2017

Using Options for Long-Horizon Off-Policy Evaluation.

Zhaohan Daniel Guo, Philip S. Thomas, Emma Brunskill

CoRR, 2017

Sample Efficient Feature Selection for Factored MDPs.

Zhaohan Daniel Guo, Emma Brunskill

CoRR, 2017

Using Options and Covariance Testing for Long Horizon Off-Policy Policy Evaluation.

Zhaohan Guo, Philip S. Thomas, Emma Brunskill

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

PAC Continuous State Online Multitask Reinforcement Learning with Identification.

Yao Liu, Zhaohan Guo, Emma Brunskill

Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016

A PAC RL Algorithm for Episodic POMDPs.

Zhaohan Daniel Guo, Shayan Doroudi, Emma Brunskill

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Concurrent PAC RL.

Zhaohan Guo, Emma Brunskill

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Joint semantic utterance classification and slot filling with recursive neural networks.

Zhaohan Daniel Guo, Gökhan Tür, Wen-tau Yih, Geoffrey Zweig

Proceedings of the 2014 IEEE Spoken Language Technology Workshop, 2014