New Advances in Statistics and Data Science

May 24-26, 2022, Honolulu, Hawaii




Genevera Allen: Graph Learning for Large-Scale Functional Neuronal Connectivity

Krishnakumar Balasubramanian: Towards a Theory of Non-Log-Concave Sampling

Jelena Bradic: Dynamic Causal Learning: Excursions in Double Robustness

Tony Cai: Transfer Learning: Optimality and Adaptive Algorithms

Yuejie Chi: Offline Reinforcement Learning: Towards Optimal Sample Complexities

David Choi: Causal inference in experiments with interference

Edgar Dobriban: T-Cal: An Optimal Test for the Calibration of Predictive Models

Simon Du: When is Offline Two-Player Zero-Sum Markov Game Solvable?

Philip Ernst: New Frontiers in Statistical Inference for Stochastic Processes

Jianqing Fan: How Do Noise Tails Impact on Deep ReLU Networks?

Yingying Fan: Asymptotic Properties of High-dimensional Random Forests

Yang Feng: Random Subspace Ensemble

Yuqi Gu: Blessing of Latent Dependence and Identifiable Deep Modeling of Discrete Latent Variables

Lucas Janson: Controlled Discovery and Localization of Signals via Bayesian Linear Programming (BLiP)

Adel Javanmard: The Curse of Overparametrization in Adversarial Training

Jiashun Jin:

Mladen Kolar: Confidence sets for Causal Discovery

Eric Laber: Safe Reinforcement Learning in mHealth

Hongzhe Lee: Estimation and Inference with Proxy Data and its Genetic Applications

Jason D. Lee: Offline Reinforcement Learning with Only Realizability

Jun S. Liu: Statistics Meet Neural Networks: Bootstrap, Cross-Validations, and Beyond

Regina Liu:

Jinchi Lv: High-Dimensional Knockoffs Inference for Time Series Data

Tengyu Ma: Understanding Self-supervised Learning

Zongming Ma: Matching of Datasets and Its Applications in Single-cell Biology

Arian Maleki: Asymptotic Analysis of SLOPE

Rajarshi Mukherjee: Causal Inference in High Dimensions

Debashis Paul: Estimation of Spectra of High-dimensional Separable Covariance Matrices

Patrick Rubin-Delanchy: Manifold Structure in Graph Embeddings

Peter XK Song: Real-time Regression Analysis of Streaming Clustered Data with Possible Abnormal Data Batches

Weijie Su: When Will You Become the Best Reviewer of Your Own Papers? An Owner-Assisted Approach to Mechanism Design

Boxiang Wang: Sparse Convoluted Rank Regression in High Dimensions

Mengdi Wang:

Wanjie Wang: Covariate-Associated Community Detection on Social Networks

Yuting Wei: Minimum L1-norm Interpolators: Precise Asymptotics and Multiple Descent

Xiufan Yu: Power-enhanced Simultaneous Test of High-dimensional Mean Vectors and Covariance Matrices with Application to Gene-set Testing.

Chunming Zhang: Maximum Independent Component Analysis with Application to Non-linear Temporal Signals

Cun-Hui Zhang: Tensor PCA in High Dimensional CP Models

Heping Zhang: Statistical Modeling and Inference of Tensor

Hongyu Zhao: Estimating Cell-type-specific Gene Co-expression Networks from Bulk Gene Expression Data with an Application to Alzheimer's Disease

Ji Zhu: