517 citations · 1.1k across the 28 of their papers we have counts for
8 papers · 1 filter
Plausible deniability for privacy-preserving data synthesis
Song Mei, Zhiqiang Ye
In the field of privacy protection, publishing complete data (especially high-dimensional data sets) is one of the most challenging problems. The common encryption technology can n…
Near-optimal multiple testing in Bayesian linear models with finite-sample FDR control
Taejoo Ahn, Licong Lin, Song Mei
In high dimensional variable selection problems, statisticians often seek to design multiple testing procedures that control the False Discovery Rate (FDR), while concurrently iden…
Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms
Fan Chen, Yu Bai, Song Mei
Partial Observability -- where agents can only observe partial information about the true underlying state of the system -- is ubiquitous in real-world applications of Reinforcemen…
Sample-Efficient Learning of Correlated Equilibria in Extensive-Form Games
Ziang Song, Song Mei, Yu Bai
Imperfect-Information Extensive-Form Games (IIEFGs) is a prevalent model for real-world games involving imperfect information and sequential plays. The Extensive-Form Correlated Eq…
Efficient Phi-Regret Minimization in Extensive-Form Games via Online Mirror Descent
Yu Bai, Chi Jin, Song Mei +2
A conceptually appealing approach for learning Extensive-Form Games (EFGs) is to convert them to Normal-Form Games (NFGs). This approach enables us to directly translate state-of-t…
Performance and limitations of the QAOA at constant levels on large sparse hypergraphs and spin glass models
Joao Basso, David Gamarnik, Song Mei +1
The Quantum Approximate Optimization Algorithm (QAOA) is a general purpose quantum algorithm designed for combinatorial optimization. We analyze its expected performance and prove…
Efficient and Differentiable Conformal Prediction with General Function Classes
Yu Bai, Song Mei, Huan Wang +2
Quantifying the data uncertainty in learning tasks is often done by learning a prediction interval or prediction set of the label given the input. Two commonly desired properties f…
Near-Optimal Learning of Extensive-Form Games with Imperfect Information
Yu Bai, Chi Jin, Song Mei +1
This paper resolves the open question of designing near-optimal algorithms for learning imperfect-information extensive-form games from bandit feedback. We present the first line o…