David Brandfonbrener

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 25

Top Topics

Reinforcement Learning

Top Venues

Publications

Kaiying Hou, David Brandfonbrener, Sham M. Kakade, Samy Jelassi, Eran Malach
Universal Length Generalization with Turing Programs. CoRR (2024)
Kenneth Li, Samy Jelassi, Hugh Zhang, Sham M. Kakade, Martin Wattenberg, David Brandfonbrener
Q-Probe: A Lightweight Approach to Reward Maximization for Language Models. CoRR (2024)
David Brandfonbrener, Hanlin Zhang, Andreas Kirsch, Jonathan Richard Schwarz, Sham M. Kakade
CoLoR-Filter: Conditional Loss Reduction Filtering for Targeted Language Model Pre-training. CoRR (2024)
David Brandfonbrener, Sibi Raja, Tarun Prasad, Chloe Loughridge, Jianang Yang, Simon Henniger, William E. Byrd, Robert Zinkov, Nada Amin
Verified Multi-Step Synthesis using Large Language Models and Monte Carlo Tree Search. CoRR (2024)
Rosie Zhao, Depen Morwani, David Brandfonbrener, Nikhil Vyas, Sham M. Kakade
Deconstructing What Makes a Good Optimizer for Language Models. CoRR (2024)
Samy Jelassi, David Brandfonbrener, Sham M. Kakade, Eran Malach
Repeat After Me: Transformers are Better than State Space Models at Copying. CoRR (2024)
David Brandfonbrener, Ofir Nachum, Joan Bruna
Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation. NeurIPS (2023)
David Brandfonbrener, Stephen Tu, Avi Singh, Stefan Welker, Chad Boodoo, Nikolai Matni, Jake Varley
Visual Backtracking Teleoperation: A Data Collection Protocol for Offline Image-Based Reinforcement Learning. ICRA (2023)
David Brandfonbrener, Ofir Nachum, Joan Bruna
Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation. CoRR (2023)
David Brandfonbrener, Alberto Bietti, Jacob Buckman, Romain Laroche, Joan Bruna
When does return-conditioned supervised learning work for offline reinforcement learning? CoRR (2022)
David Brandfonbrener, Alberto Bietti, Jacob Buckman, Romain Laroche, Joan Bruna
When does return-conditioned supervised learning work for offline reinforcement learning? NeurIPS (2022)
Denis Yarats, David Brandfonbrener, Hao Liu, Michael Laskin, Pieter Abbeel, Alessandro Lazaric, Lerrel Pinto
Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning. CoRR (2022)
David Brandfonbrener, Stephen Tu, Avi Singh, Stefan Welker, Chad Boodoo, Nikolai Matni, Jake Varley
Visual Backtracking Teleoperation: A Data Collection Protocol for Offline Image-Based Reinforcement Learning. CoRR (2022)
David Brandfonbrener, Remi Tachet des Combes, Romain Laroche
Incorporating Explicit Uncertainty Estimates into Deep Offline Reinforcement Learning. CoRR (2022)
David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna
Quantile Filtered Imitation Learning. CoRR (2021)
David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna
Offline RL Without Off-Policy Evaluation. CoRR (2021)
David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna
Offline Contextual Bandits with Overparameterized Models. ICML (2021)
David Brandfonbrener, Will Whitney, Rajesh Ranganath, Joan Bruna
Offline RL Without Off-Policy Evaluation. NeurIPS (2021)
David Brandfonbrener, Joan Bruna
Geometric Insights into the Convergence of Nonlinear TD Learning. ICLR (2020)
David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna
Overfitting and Optimization in Offline Policy Learning. CoRR (2020)
Andrea Zanette, David Brandfonbrener, Emma Brunskill, Matteo Pirotta, Alessandro Lazaric
Frequentist Regret Bounds for Randomized Least-Squares Value Iteration. AISTATS (2020)
William F. Whitney, Min Jae Song, David Brandfonbrener, Jaan Altosaar, Kyunghyun Cho
Evaluating representations by the complexity of learning low-loss predictors. CoRR (2020)
David Brandfonbrener, Joan Bruna
On the Expected Dynamics of Nonlinear TD Learning. CoRR (2019)
Andrea Zanette, David Brandfonbrener, Matteo Pirotta, Alessandro Lazaric
Frequentist Regret Bounds for Randomized Least-Squares Value Iteration. CoRR (2019)
David Brandfonbrener, Pat Devlin, Netanel Friedenberg, Yuxuan Ke, Steffen Marcus, Henry Reichard, Ethan Sciamma
Two-Vertex Generators of Jacobians of Graphs. Electron. J. Comb. 25 (1) (2018)