Binghui Peng

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 64

Top Topics

Sponsored Search Auctions

Influence Maximization

Directed Networks

Top Venues

Publications

Binghui Peng, Aviad Rubinstein
The complexity of approximate (coarse) correlated equilibrium for incomplete information games. COLT (2024)
Binghui Peng
The sample complexity of multi-distribution learning. COLT (2024)
Binghui Peng, Srini Narayanan, Christos H. Papadimitriou
On Limitations of the Transformer Architecture. CoRR (2024)
Binghui Peng, Christos H. Papadimitriou
The complexity of non-stationary reinforcement learning. ALT (2024)
Binghui Peng, Aviad Rubinstein
Fast Swap Regret Minimization and Applications to Approximate Correlated Equilibria. STOC (2024)
Binghui Peng, Aviad Rubinstein
The complexity of approximate (coarse) correlated equilibrium for incomplete information games. CoRR (2024)
Xi Chen, Binghui Peng
Complexity of Equilibria in First-Price Auctions under General Tie-Breaking Rules. CoRR (2023)
Binghui Peng, Aviad Rubinstein
Fast swap regret minimization and applications to approximate correlated equilibria. CoRR (2023)
Binghui Peng, Fred Zhang
Online Prediction in Sub-linear Space. SODA (2023)
Binghui Peng, Aviad Rubinstein
Fully-dynamic-to-incremental reductions with known deletion order (e.g. sliding window). SOSA (2023)
Sara Ahmadian, Hossein Esfandiari, Vahab Mirrokni, Binghui Peng
Robust Load Balancing with Machine Learned Advice. J. Mach. Learn. Res. 24 (2023)
Xi Chen, Binghui Peng
Memory-Query Tradeoffs for Randomized Convex Optimization. CoRR (2023)
Christos H. Papadimitriou, Binghui Peng
Public goods games in directed networks. Games Econ. Behav. 139 (2023)
Xi Chen, Binghui Peng
Complexity of Equilibria in First-Price Auctions under General Tie-Breaking Rules. STOC (2023)
Xi Chen, Binghui Peng
Memory-Query Tradeoffs for Randomized Convex Optimization. FOCS (2023)
Shunhua Jiang, Binghui Peng, Omri Weinstein
The Complexity of Dynamic Least-Squares Regression. FOCS (2023)
Binghui Peng, Aviad Rubinstein
Near Optimal Memory-Regret Tradeoff for Online Learning. FOCS (2023)
Ilan Reuven Cohen, Binghui Peng
Primal-Dual Schemes for Online Matching in Bounded Degree Graphs. ESA (2023)
Binghui Peng
The sample complexity of multi-distribution learning. CoRR (2023)
Binghui Peng, Aviad Rubinstein
Near Optimal Memory-Regret Tradeoff for Online Learning. CoRR (2023)
Christos H. Papadimitriou, Binghui Peng
The complexity of non-stationary reinforcement learning. CoRR (2023)
Xi Chen, Binghui Peng
On the complexity of dynamic submodular maximization. STOC (2022)
Xi Chen, Christos H. Papadimitriou, Binghui Peng
Memory Bounds for Continual Learning. FOCS (2022)
Binghui Peng, Andrej Risteski
Continual learning: a feature extraction formalization, an efficient algorithm, and fundamental obstructions. NeurIPS (2022)
Sara Ahmadian, Hossein Esfandiari, Vahab S. Mirrokni, Binghui Peng
Robust Load Balancing with Machine Learned Advice. SODA (2022)
Xi Chen, Christos H. Papadimitriou, Binghui Peng
Memory Bounds for Continual Learning. CoRR (2022)
Shunhua Jiang, Binghui Peng, Omri Weinstein
Dynamic Least-Squares Regression. CoRR (2022)
Binghui Peng, Fred Zhang
Online Prediction in Sub-linear Space. CoRR (2022)
Thomas Chen, Xi Chen, Binghui Peng, Mihalis Yannakakis
Computational Hardness of the Hylland-Zeckhauser Scheme. SODA (2022)
Wei Chen, Binghui Peng, Grant Schoenebeck, Biaoshuai Tao
Adaptive Greedy versus Non-adaptive Greedy for Influence Maximization. J. Artif. Intell. Res. 74 (2022)
Binghui Peng, Andrej Risteski
Continual learning: a feature extraction formalization, an efficient algorithm, and fundamental obstructions. CoRR (2022)
Albert Cheu, Matthew Joseph, Jieming Mao, Binghui Peng
Shuffle Private Stochastic Convex Optimization. ICLR (2022)
Binghui Peng, Aviad Rubinstein
Fully-dynamic-to-incremental reductions with known deletion order (e.g. sliding window). CoRR (2022)
Binghui Peng
Dynamic Influence Maximization. CoRR (2021)
Sara Ahmadian, Allen Liu, Binghui Peng, Morteza Zadimoghaddam
Distributed Load Balancing: A New Framework and Improved Guarantees. ITCS (2021)
Shunyu Yao, Binghui Peng, Christos H. Papadimitriou, Karthik Narasimhan
Self-Attention Networks Can Process Bounded Hierarchical Languages. CoRR (2021)
Binghui Peng
Dynamic influence maximization. NeurIPS (2021)
Christos H. Papadimitriou, Binghui Peng
Public Goods Games in Directed Networks. EC (2021)
Christos H. Papadimitriou, Binghui Peng
Public Good Games in Directed Networks. CoRR (2021)
Xi Chen, Binghui Peng
On the Complexity of Dynamic Submodular Maximization. CoRR (2021)
Shunyu Yao, Binghui Peng, Christos H. Papadimitriou, Karthik Narasimhan
Self-Attention Networks Can Process Bounded Hierarchical Languages. ACL/IJCNLP (1) (2021)
Albert Cheu, Matthew Joseph, Jieming Mao, Binghui Peng
Shuffle Private Stochastic Convex Optimization. CoRR (2021)
Jan van den Brand, Binghui Peng, Zhao Song, Omri Weinstein
Training (Overparametrized) Neural Networks in Near-Linear Time. ITCS (2021)
Beidi Chen, Zichang Liu, Binghui Peng, Zhaozhuo Xu, Jonathan Lingjie Li, Tri Dao, Zhao Song, Anshumali Shrivastava, Christopher Ré
MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training. ICLR (2021)
Thomas Chen, Xi Chen, Binghui Peng, Mihalis Yannakakis
Computational Hardness of the Hylland-Zeckhauser Scheme. CoRR (2021)
Xiaoxiao Li, Yangsibo Huang, Binghui Peng, Zhao Song, Kai Li
MixCon: Adjusting the Separability of Data Representations for Harder Data Recovery. CoRR (2020)
Wei Chen, Binghui Peng, Grant Schoenebeck, Biaoshuai Tao
Adaptive Greedy versus Non-Adaptive Greedy for Influence Maximization. AAAI (2020)
Xi Chen, Binghui Peng
Hedging in games: Faster convergence of external and swap regrets. NeurIPS (2020)
Jan van den Brand, Binghui Peng, Zhao Song, Omri Weinstein
Training (Overparametrized) Neural Networks in Near-Linear Time. CoRR (2020)
Xi Chen, Binghui Peng
Hedging in games: Faster convergence of external and swap regrets. CoRR (2020)
Weiran Shen, Binghui Peng, Hanpeng Liu, Michael Zhang, Ruohan Qian, Yan Hong, Zhi Guo, Zongyao Ding, Pengjun Lu, Pingzhong Tang
Reinforcement Mechanism Design: With Applications to Dynamic Pricing in Sponsored Search Auctions. AAAI (2020)
Anupam Gupta, Guru Guruganesh, Binghui Peng, David Wajc
Stochastic Online Metric Matching. ICALP (2019)
Ilan Reuven Cohen, Binghui Peng, David Wajc
Tight Bounds for Online Edge Coloring. FOCS (2019)
Binghui Peng, Wei Chen
Adaptive Influence Maximization with Myopic Feedback. NeurIPS (2019)
Binghui Peng, Wei Chen
Adaptive Influence Maximization with Myopic Feedback. CoRR (2019)
Binghui Peng, Weiran Shen, Pingzhong Tang, Song Zuo
Learning Optimal Strategies to Commit To. AAAI (2019)
Anupam Gupta, Guru Guruganesh, Binghui Peng, David Wajc
Stochastic Online Metric Matching. CoRR (2019)
Ilan Reuven Cohen, Binghui Peng, David Wajc
Tight Bounds for Online Edge Coloring. CoRR (2019)
Zhiyi Huang, Binghui Peng, Zhihao Gavin Tang, Runzhou Tao, Xiaowei Wu, Yuhao Zhang
Tight Competitive Ratios of Classic Matching Algorithms in the Fully Online Model. SODA (2019)
Wei Chen, Binghui Peng
On Adaptivity Gaps of Influence Maximization Under the Independent Cascade Model with Full-Adoption Feedback. ISAAC (2019)
Wei Chen, Binghui Peng, Grant Schoenebeck, Biaoshuai Tao
Adaptive Greedy versus Non-adaptive Greedy for Influence Maximization. CoRR (2019)
Wei Chen, Binghui Peng
On Adaptivity Gaps of Influence Maximization under the Independent Cascade Model with Full Adoption Feedback. CoRR (2019)
Zhiyi Huang, Binghui Peng, Zhihao Gavin Tang, Runzhou Tao, Xiaowei Wu, Yuhao Zhang
Tight Competitive Ratios of Classic Matching Algorithms in the Fully Online Model. CoRR (2018)
Weiran Shen, Binghui Peng, Hanpeng Liu, Michael Zhang, Ruohan Qian, Yan Hong, Zhi Guo, Zongyao Ding, Pengjun Lu, Pingzhong Tang
Reinforcement Mechanism Design, with Applications to Dynamic Pricing in Sponsored Search Auctions. CoRR (2017)