Peng, Binghui

16 publications

ICML 2025 A near Linear Query Lower Bound for Submodular Maximization Binghui Peng, Aviad Rubinstein

COLT 2024 The Complexity of Approximate (coarse) Correlated Equilibrium for Incomplete Information Games Binghui Peng, Aviad Rubinstein

ALT 2024 The Complexity of Non-Stationary Reinforcement Learning Binghui Peng, Christos Papadimitriou

COLT 2024 The Sample Complexity of Multi-Distribution Learning Binghui Peng

JMLR 2023 Robust Load Balancing with Machine Learned Advice Sara Ahmadian, Hossein Esfandiari, Vahab Mirrokni, Binghui Peng

JAIR 2022 Adaptive Greedy Versus Non-Adaptive Greedy for Influence Maximization Wei Chen, Binghui Peng, Grant Schoenebeck, Biaoshuai Tao

NeurIPS 2022 Continual Learning: A Feature Extraction Formalization, an Efficient Algorithm, and Fundamental Obstructions Binghui Peng, Andrej Risteski

NeurIPSW 2022 Memory Bounds for Continual Learning Binghui Peng, Xi Chen, Christos Papadimitriou

ICLR 2022 Shuffle Private Stochastic Convex Optimization Albert Cheu, Matthew Joseph, Jieming Mao, Binghui Peng

NeurIPS 2021 Dynamic Influence Maximization Binghui Peng

ICLR 2021 MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training Beidi Chen, Zichang Liu, Binghui Peng, Zhaozhuo Xu, Jonathan Lingjie Li, Tri Dao, Zhao Song, Anshumali Shrivastava, Christopher Re

AAAI 2020 Adaptive Greedy Versus Non-Adaptive Greedy for Influence Maximization Wei Chen, Binghui Peng, Grant Schoenebeck, Biaoshuai Tao

NeurIPS 2020 Hedging in Games: Faster Convergence of External and Swap Regrets Xi Chen, Binghui Peng

AAAI 2020 Reinforcement Mechanism Design: With Applications to Dynamic Pricing in Sponsored Search Auctions Weiran Shen, Binghui Peng, Hanpeng Liu, Michael Zhang, Ruohan Qian, Yan Hong, Zhi Guo, Zongyao Ding, Pengjun Lu, Pingzhong Tang

NeurIPS 2019 Adaptive Influence Maximization with Myopic Feedback Binghui Peng, Wei Chen

AAAI 2019 Learning Optimal Strategies to Commit to Binghui Peng, Weiran Shen, Pingzhong Tang, Song Zuo