Sotabase

Career

· Assistant Professor, University of Maryland2026–
· PhD in Computer Science, Columbia University2019–2024
· Visiting Faculty Researcher, Google Research
· Postdoctoral Researcher, Simons Institute, UC Berkeley
· Postdoctoral Research Fellow, Stanford University
· Bachelor's degree, Tsinghua University

Publications (35)

Self-Attention Networks Can Process Bounded Hierarchical Languages
Annual Meeting of the Association for Computational Linguistics · 2021
100
cited
Training (Overparametrized) Neural Networks in Near-Linear Time
Information Technology Convergence and Services · 2020
82
cited
Hedging in games: Faster convergence of external and swap regrets
Neural Information Processing Systems · 2020
75
cited
Learning Optimal Strategies to Commit To
AAAI Conference on Artificial Intelligence · 2019
67
cited
MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training
International Conference on Learning Representations · 2021
63
cited
Tight Competitive Ratios of Classic Matching Algorithms in the Fully Online Model
ACM-SIAM Symposium on Discrete Algorithms · 2018
61
cited
Reinforcement Mechanism Design, with Applications to Dynamic Pricing in Sponsored Search Auctions
arXiv.org · 2017
58
cited
Tight Bounds for Online Edge Coloring
IEEE Annual Symposium on Foundations of Computer Science · 2019
37
cited
Stochastic Online Metric Matching
International Colloquium on Automata, Languages and Programming · 2019
32
cited
Adaptive Influence Maximization with Myopic Feedback
Neural Information Processing Systems · 2019
31
cited
Public Goods Games in Directed Networks
ACM Conference on Economics and Computation · 2021
29
cited
Shuffle Private Stochastic Convex Optimization
International Conference on Learning Representations · 2021
29
cited
Adaptive Greedy versus Non-adaptive Greedy for Influence Maximization
AAAI Conference on Artificial Intelligence · 2019
26
cited
Memory Bounds for Continual Learning
IEEE Annual Symposium on Foundations of Computer Science · 2022
25
cited
Dynamic Influence Maximization
Neural Information Processing Systems · 2021
24
cited
On the complexity of dynamic submodular maximization
Symposium on the Theory of Computing · 2021
19
cited
On Adaptivity Gaps of Influence Maximization under the Independent Cascade Model with Full Adoption Feedback
International Symposium on Algorithms and Computation · 2019
17
cited
Computational Hardness of the Hylland-Zeckhauser Scheme
ACM-SIAM Symposium on Discrete Algorithms · 2021
16
cited
Online Prediction in Sub-linear Space
ACM-SIAM Symposium on Discrete Algorithms · 2022
16
cited
Robust Load Balancing with Machine Learned Advice
ACM-SIAM Symposium on Discrete Algorithms · 2022
14
cited
Sotabase
Binghui Peng | Researcher Profile | Sotabase | Sotabase