Yu Bai
Affiliations:- Salesforce Research, Palo Alto, CA, USA
- Stanford University, CA, USA (PhD 2019)
According to our database1,
Yu Bai
authored at least 45 papers
between 2019 and 2023.
Collaborative distances:
Collaborative distances:
Timeline
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Online presence:
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on yubai.org
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on twitter.com
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on github.com
On csauthors.net:
Bibliography
2023
CoRR, 2023
How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representations.
CoRR, 2023
Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining.
CoRR, 2023
CoRR, 2023
Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection.
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Breaking the Curse of Multiagency: Provably Efficient Decentralized Multi-Agent RL with Function Approximation.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023
2022
Unified Algorithms for RL with Decision-Estimation Coefficients: No-Regret, PAC, and Reward-Free Learning.
CoRR, 2022
CoRR, 2022
Proceedings of the Uncertainty in Artificial Intelligence, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the International Conference on Machine Learning, 2022
When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently?
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022
2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Exact Gap between Generalization Error and Uniform Convergence in Random Feature Models.
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Don't Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary Classification.
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
2020
Near Optimal Provable Uniform Convergence in Off-Policy Evaluation for Reinforcement Learning.
CoRR, 2020
Taylorized Training: Towards Better Approximation of Neural Network Training at Finite Width.
CoRR, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Beyond Linearization: On Quadratic and Higher-Order Approximation of Wide Neural Networks.
Proceedings of the 8th International Conference on Learning Representations, 2020
2019
Proximal algorithms for constrained composite optimization, with applications to solving low-rank SDPs.
CoRR, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the 7th International Conference on Learning Representations, 2019
Proceedings of the 7th International Conference on Learning Representations, 2019
Proceedings of the 7th International Conference on Learning Representations, 2019