| Self-Attention Networks Can Process Bounded Hierarchical Languages S Yao, B Peng, C Papadimitriou, K Narasimhan The 59th Annual Meeting of the Association for Computational Linguistics …, 2021 | 136 | 2021 |
| Training (overparametrized) neural networks in near-linear time J Brand, B Peng, Z Song, O Weinstein arXiv preprint arXiv:2006.11648, 2020 | 99 | 2020 |
| Mongoose: A learnable lsh framework for efficient neural network training B Chen, Z Liu, B Peng, Z Xu, JL Li, T Dao, Z Song, A Shrivastava, C Re International Conference on Learning Representations, 2020 | 96 | 2020 |
| Hedging in games: Faster convergence of external and swap regrets X Chen, B Peng Thirty-fourth Advances in Neural Information Processing Systems, 2020 | 91 | 2020 |
| Learning optimal strategies to commit to B Peng, W Shen, P Tang, S Zuo Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 2149-2156, 2019 | 82 | 2019 |
| Reinforcement mechanism design: With applications to dynamic pricing in sponsored search auctions W Shen, B Peng, H Liu, M Zhang, R Qian, Y Hong, Z Guo, Z Ding, P Lu, ... Proceedings of the AAAI conference on artificial intelligence 34 (02), 2236-2243, 2020 | 80 | 2020 |
| On limitations of the transformer architecture B Peng, S Narayanan, C Papadimitriou Collegium Beatus Rhenanus, 2024 | 79 | 2024 |
| Tight competitive ratios of classic matching algorithms in the fully online model Z Huang, B Peng, ZG Tang, R Tao, X Wu, Y Zhang Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete …, 2019 | 78 | 2019 |
| Fast swap regret minimization and applications to approximate correlated equilibria B Peng, A Rubinstein Proceedings of the 56th Annual ACM Symposium on Theory of Computing, 1223-1234, 2024 | 49 | 2024 |
| Tight bounds for online edge coloring IR Cohen, B Peng, D Wajc 2019 IEEE 60th Annual Symposium on Foundations of Computer Science (FOCS), 1-25, 2019 | 47 | 2019 |
| Stochastic online metric matching A Gupta, G Guruganesh, B Peng, D Wajc 46th International Colloquium on Automata, Languages, and Programming (ICALP …, 2019 | 44 | 2019 |
| Adaptive influence maximization with myopic feedback B Peng, W Chen Advances in Neural Information Processing Systems 32, 2019 | 44 | 2019 |
| Public Good Games in Directed Networks C Papadimitriou, B Peng The Twenty-Second ACM Conference on Economics and Computation (EC 2021), 2021 | 39 | 2021 |
| Adaptive greedy versus non-adaptive greedy for influence maximization W Chen, B Peng, G Schoenebeck, B Tao Journal of Artificial Intelligence Research 74, 303-351, 2022 | 38 | 2022 |
| Memory bounds for continual learning X Chen, C Papadimitriou, B Peng 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS …, 2022 | 37 | 2022 |
| Dynamic influence maximization B Peng Advances in Neural Information Processing Systems 34, 10718-10731, 2021 | 34 | 2021 |
| Shuffle private stochastic convex optimization A Cheu, M Joseph, J Mao, B Peng arXiv preprint arXiv:2106.09805, 2021 | 34 | 2021 |
| Theoretical limitations of multi-layer transformer L Chen, B Peng, H Wu arXiv preprint arXiv:2412.02975, 2024 | 24 | 2024 |
| Online prediction in sub-linear space B Peng, F Zhang Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2023 | 24 | 2023 |
| Computational Hardness of the Hylland-Zeckhauser Scheme∗ T Chen, X Chen, B Peng, M Yannakakis Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2022 | 24 | 2022 |
Christos H PAPADIMITRIOUColumbia UniversityVerified email at columbia.edu
