@misc{myers2025horizon,
author = {Myers, Vivek and Ji, Catherine and Eysenbach, Benjamin},
eprint = {2501.02709},
eprinttype = {arXiv},
howpublished = {arXiv:2501.02709},
title = {{Horizon Generalization} in {Reinforcement Learning}},
url = {https://arxiv.org/abs/2501.02709},
year = {2025},
}
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Vivek Myers
I’m a PhD student at Berkeley Artificial Intelligence Research (BAIR) advised by Anca Dragan and Sergey Levine with support from an NDSEG fellowship. My research interests include reinforcement learning, human-AI interaction, and robotics. Before coming to Berkeley, I got my bachelor's degree in Computer Science and Mathematics at Stanford University, where I worked with Dorsa Sadigh. |
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Preprints |
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Horizon Generalization in Reinforcement Learning
2025
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Accelerating Goal-Conditioned RL Algorithms and Research
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2024
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Publications |
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Learning to Assist Humans without Inferring Rewards
Conference on Neural Information Processing Systems (NeurIPS), 2024
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2024
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Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference
Conference on Neural Information Processing Systems (NeurIPS), 2024
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2024
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Policy Adaptation via Language Optimization: Decomposing Tasks for Few-Shot Imitation
Conference on Robot Learning (CoRL), 2024
×
2024
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Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making
International Conference on Machine Learning (ICML), 2024
×
2024
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Coprocessor Actor Critic: A Model-Based Reinforcement Learning Approach For Adaptive Brain Stimulation
International Conference on Machine Learning (ICML), 2024
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2024
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BridgeData V2: A Dataset for Robot Learning at Scale
Conference on Robot Learning (CoRL), 2023
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2023
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Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control
Conference on Robot Learning (CoRL), 2023
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2023
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Active Reward Learning from Online Preferences
IEEE International Conference on Robotics and Automation (ICRA), 2023
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2023
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Learning Multimodal Rewards from Rankings
Conference on Robot Learning (CoRL), 2021
(Oral Presentation)
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2021
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Effective Surrogate Models for Protein Design with Bayesian Optimization
ICML 2021 Workshop on Computational Biology
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2021
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A Hierarchical Approach to Scaling Batch Active Search Over Structured Data
ICML 2020 Workshop on Real World Experiment Design and Active Learning
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2020
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equal contribution
equal advising
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