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Activity Details


2 ! 		Sun, 8/8/2021, 1:30 PM - 3:20 PM Virtual
When Causal Inference Meets Reinforcement Learning: The Story of Mobile-Delivered Interventions — Invited Papers
IMS, ENAR, Biometrics Section
Organizer(s): Min Qian, Columbia University
Chair(s): Chengchun Shi, LSE
1:35 PM Assessing Time-Varying Causal Effects in the Presence of Cluster-Level Treatment Effect Heterogeneity
Jieru Hera Shi, University of Michigan, Ann Arbor; Zhenke Wu, University of Michigan, Ann Arbor; Walter Dempsey, University of Michigan
2:00 PM Policy Evaluation Under Interference
Stefan Wager, Stanford University
2:25 PM We Used RL, but … Did It Work?!
Peng Liao, Harvard University; Susan Murphy, Harvard University; Predrag Klasnja, University of Michigan
2:50 PM Discussant: Michael Kosorok, University of North Carolina at Chapel Hill
3:10 PM Floor Discussion
 
 

10 ! 		Sun, 8/8/2021, 1:30 PM - 3:20 PM Virtual
Advances in Functional and Geometric Data Analysis — Invited Papers
IMS
Organizer(s): Fang Yao, Peking University
Chair(s): Yichao Wu, University of Illinois at Chicago
1:35 PM Intrinsic Riemannian Functional Data Analysis for Sparse Longitudinal Data
Zhenhua Lin, National University of Singapore; Lingxuan Shao, Peking University; Fang Yao, Peking University
2:00 PM Unified Principal Component Analysis for Sparse and Dense Functional Data Under Spatial Dependency
Yehua Li, University of California, Riverside
2:25 PM Basis Expansions for Functional Snippets
Zhenhua Lin, National University of Singapore; Jane-Ling Wang, UC Davis; Qixian Zhong, Tsing Hua University
2:50 PM Wasserstein Regression for Distributions, with Application to Distributional Time Series
Hans-Georg Müller, University of California, Davis; Yaqing Chen , University of California, Davis ; Zhenhua Lin, National University of Singapore
3:15 PM Floor Discussion
 
 

12 * ! 		Sun, 8/8/2021, 1:30 PM - 3:20 PM Virtual
High-Dimensional Parameter Learning on Spatio-Temporal Hidden Markov Models and Its Applications in Epidemiology — Invited Papers
IMS, Section on Statistics in Epidemiology, General Methodology
Organizer(s): Ning Ning, University of Michigan, Ann Arbor
Chair(s): Ning Ning, University of Michigan, Ann Arbor
1:35 PM Modeling Epidemic Control Using Markovian and Non-Markovian Partially Observed Systems
Ya'acov Ritov, University of Michigan; Hamid Eftekhari, University of Michigan; Debarghya Mukherjee, University of MIchigan; Moulinath Banerjee, University of Michigan
1:50 PM Bagged filters for inference on metapopulation dynamics, with epidemiological applications
Edward L Ionides, University of Michigan, Ann Arbor
2:05 PM A Bayesian Spatio-Temporal Approach for Estimating County-Level Opioid Misuse Rates in Ohio
Staci Hepler, Wake Forest University; David Kline, The Ohio State University; Lance Waller, Emory University
2:20 PM An Approximate Joint Distribution for Stochastic Differential Equations, with Application to Modeling the COVID-19 Epidemic in Pennsylvania, Rhode Island, and Massachusetts
Ephraim Hanks, Penn State University
2:35 PM Understanding Complex and Fine-Scale Animal Behavior with Hidden Markov Models
Marie Auger-Methe, The University of British Columbia; Ron R Togunov, The University of British Columbia; Nancy Heckman, The University of British Columbia; Evan Sidrow, The University of British Columbia
2:50 PM Partially Observed Time Series Models Using Long Short-Term Memory Models
Yves Atchade, Boston University
3:05 PM Floor Discussion
 
 

19 ! 		Sun, 8/8/2021, 1:30 PM - 3:20 PM Virtual
Statistical Inference for Random Networks and Matrices — Topic-Contributed Papers
Section on Nonparametric Statistics, IMS, International Chinese Statistical Association
Organizer(s): Min Xu, Rutgers University
Chair(s): Tengyao Wang, University College London
1:35 PM Testing Correlation of Unlabeled Random Graphs Presentation
Yihong Wu, Yale; Jiaming Xu, Duke University; Sophie H. Yu, Duke University
1:55 PM Asymptotic Distributions of High-Dimensional Distance Correlation Inference Presentation
Lan Gao, University of Southern California; Yingying Fan, University of Southern California; Jinchi Lv, University of Southern California; Qi-Man Shao, Southern University of Science and Technology and The Chinese University of Hong Kong
2:15 PM Euclidean Representation of Low-Rank Matrices and Intrinsic Perturbation Analysis with Applications to High-Dimensional Statistics
Fangzheng Xie, Indiana University
2:35 PM Inference on the History of Infection Networks
Min Xu, Rutgers University; Harry Crane, Rutgers University
2:55 PM Spectral Analysis of Networks with Latent Space Dynamics and Signs
Joshua Cape, University of Pittsburgh
3:15 PM Floor Discussion
 
 

31 ! 		Sun, 8/8/2021, 3:30 PM - 5:20 PM Virtual
Recent Developments in Learning Across Environments — Invited Papers
IMS, International Indian Statistical Association, Section on Statistical Learning and Data Science, Caucus for Women in Statistics
Organizer(s): Moulinath Banerjee, University of Michigan
Chair(s): Bodhisattva Sen, Columbia University
3:35 PM Adaptive Transfer Learning
Richard J. Samworth, University of Cambridge; Henry Reeve, Bristol University; Timothy Cannings, University of Edinburgh
4:00 PM Some Recent Insights on Transfer-Learning
Samory K. Kpotufe, Columbia University
4:25 PM There Is No Trade-Off: Enforcing Fairness Can Improve Accuracy
Yuekai Sun, University of Michigan
4:50 PM Discussant: Moulinath Banerjee, University of Michigan
5:10 PM Floor Discussion
 
 

33 		Sun, 8/8/2021, 3:30 PM - 5:20 PM Virtual
Sensitivity Analysis with Nonignorable Missing Data: Recent Work from Academia, Industry, and Regulatory Agencies — Invited Papers
ENAR, IMS, Society for Clinical Trials
Organizer(s): Shu Yang, North Carolina State University
Chair(s): Shu Yang, North Carolina State University
3:35 PM Sensitivity Analysis Applications in Some Regulatory Experience
Eiji Ishida, FDA
4:00 PM Control-Based Imputation in Longitudinal Clinical Trials for Continuous Outcomes with Outliers
G. Frank Liu, Merck Sharp & Dohme Corp.; Yilong Zhang, Merck & Co., Inc.; Gregory Golm, Merck & Co., Inc.
4:25 PM Global Sensitivity Analysis of Randomized Trials with Non-Monotone Missing Binary Outcomes: Application to Studies of Substance Use Disorders
Daniel Scharfstein, University of Utah
4:50 PM Discussant: Roderick Joseph Little, University of Michigan
5:10 PM Floor Discussion
 
 

38 ! 		Sun, 8/8/2021, 3:30 PM - 5:20 PM Virtual
Inference, Optimization, and Computation on Discrete Structures — Invited Papers
IMS
Organizer(s): Guanyang Wang, Rutgers University
Chair(s): Guanyang Wang, Rutgers University
3:35 PM A Multi-Resolution Theory for Approximating Infinite-P-Zero-N: Transitional Inference, Individualized Predictions, and a World Without Bias-Variance Trade-Off
Xinran Li, University of Illinois; Xiao-Li Meng, Harvard University
3:55 PM Wasserstein gradient flow and Estimation of Gaussian Mixtures
Harrison Zhou, Yale University
4:15 PM Spectral gaps and error estimates for infinite-dimensional Metropolis-Hastings with non-Gaussian priors
James Johndrow, University of Pennsylvania; Bamdad Hosseini, California Institute of Technology
4:35 PM Bayesian Pyramids: Identifying Interpretable Discrete Latent Structures from Discrete Data
Yuqi Gu, Columbia University; David Dunson, Duke University
4:55 PM Statistical Summaries of Unlabeled Evolutionary Trees
Samyak Rajanala, Stanford University; Julia A. Palacios, Stanford University
5:15 PM Floor Discussion
 
 

41 * ! 		Sun, 8/8/2021, 3:30 PM - 5:20 PM Virtual
Storytelling on COVID-19 Impact Using Experts' Prior Knowledge and Data from Social Media, Official Clinical Data, Digital Phenotype from Smartphones' Raw Sensor Data, and Emergency Departments — Invited Papers
International Society for Bayesian Analysis (ISBA), IMS, Royal Statistical Society, Caucus for Women in Statistics
Organizer(s): Kerrie Mengersen, Queensland University of Technology
Chair(s): TBD TBD, TBD
3:35 PM Predicting the Impact of COVID-19 on the Emergency Departments in Lombardy, Italy
Antonietta Mira, Università della Svizzera italiana and University of Insubria; Giulia Ghilardi, Istituto di Ricerche Farmacologiche Mario Negri IRCCS; Greta Carrara, Istituto di Ricerche Farmacologiche Mario Negri IRCCS; Angela Andreella, University of Insubria; Spyros Balafas, University of Insubria; Fabrizio Ruggeri, CNR IMATI ; Ernst C Wit, Universita della Svizzera italiana; Livio Finos, University of Padova; Guido Bertolini, Laboratory of clinical epidemiology; Giovanni Nattino, Istituto di Ricerche Farmacologiche Mario Negri IRCCS
4:00 PM COVID-19 and the Perils of Inferring Epidemiological Parameters from Clinical Data
Ernst C Wit, Universita della Svizzera italiana
4:25 PM Characterizing Lived Experiences of Highly Vulnerable Populations Through COVID-19
Jukka-Pekka Onnela, Harvard University
4:50 PM Fusing Tweets, Confirmed Cases, and Death Data to Accurately Now-Cast for COVID-19
Conor Michael Rosato, University of Liverpool; Matthew Carter, University of Liverpool; Robert Moore, University of Liverpool; John Heap, University of Liverpool; Simon Maskell, University of Liverpool; Jose Storopoli, UNINOVE - Sao Paulo - Brazil
5:15 PM Floor Discussion
 
 

42 ! 		Sun, 8/8/2021, 3:30 PM - 5:20 PM Virtual
Analysis of Dynamic High-Dimensional Data — Invited Papers
IMS, Business and Economic Statistics Section, JBES-Journal of Business & Economic Statistics
Organizer(s): Han Xiao, Rutgers, The State University of New Jersey
Chair(s): Daniel Kowal, Rice University
3:35 PM Autoregressive Networks
Qiwei Yao, London School of Economics and Political Science
4:00 PM Functional Autoregressive Processes via Reproducing Kernel Hilbert Spaces
Daren Wang, University of Notre Dame
4:25 PM Hierarchical Regime Switching Dynamic Matrix Factor Models for Modeling Mouse Motion Behavior
Rong Chen, Rutgers University
4:50 PM A Fully Online Approach for Covariance Matrices Estimation of Stochastic Gradient Descent Solutions
Wei Biao Wu, U Chicago; Wanrong Zhu, U Chicago; Xi Chen, NYU
5:25 PM Discussant: Han Xiao, Rutgers, The State University of New Jersey
5:15 PM Floor Discussion
 
 

47 ! 		Sun, 8/8/2021, 3:30 PM - 5:20 PM Virtual
Geometric and Topological Information in Data Analysis — Topic-Contributed Papers
IMS, Section on Statistical Learning and Data Science, Section on Statistics in Imaging
Organizer(s): Hengrui Luo, Lawrence Berkeley National Laboratory
Chair(s): Chul Moon, Southern Methodist University
3:35 PM Characterizing Heterogenous Information in Persistent Homology with Applications to Molecular Structure Modeling
Zixuan Cang, University of California, Irvine; Guowei Wei, Michigan State Univesity
3:55 PM Gromov-Wasserstein Learning in a Riemannian Framework
Samir Chowdhury, Stanford University
4:15 PM Density Estimation and Modeling on Symmetric Spaces
Didong Li, Princeton University; Yulong Lu, University of Massachusetts Amherst; Emmanuel Chevallier, Aix Marseille University; David Dunson, Duke University
4:35 PM Convergence of Persistence Diagram in the Subcritical Regime
Takashi Owada, Purdue University, Department of Statistics
4:55 PM Combining Geometric and Topological Information for Boundary Estimation
Justin Strait, University of Georgia; Hengrui Luo, Lawrence Berkeley National Laboratory
Discussant: Hengrui Luo, Lawrence Berkeley National Laboratory
5:15 PM Floor Discussion
 
 

63 		Mon, 8/9/2021, 10:00 AM - 11:50 AM Virtual
Inference and Interpretability in a Model-Free Setting — Invited Papers
IMS
Organizer(s): Rina Foygel Barber, University of Chicago
Chair(s): Rina Foygel Barber, University of Chicago
10:05 AM Cross-Validation Confidence Intervals for Test Error Presentation
Lester Mackey, Microsoft Research New England; Pierre Bayle, Princeton University; Alexandre Bayle, Harvard University; Lucas Janson, Harvard University
10:30 AM A Distribution-Free Test of Covariate Shift Using Conformal Prediction
Jing Lei, Carnegie Mellon University; Xiaoyu Hu, Peking University
10:55 AM A Simple Measure of Conditional Dependence
Mona Azadkia, ETH ; Sourav Chatterjee, Stanford University
11:20 AM Interpreting deep neural networks in a transformed domain
Wooseok Ha, UC Berkeley
11:45 AM Floor Discussion
 
 

72 ! 		Mon, 8/9/2021, 10:00 AM - 11:50 AM Virtual
Testing and estimation using betting, e-values and martingales — Invited Papers
IMS, Royal Statistical Society, International Statistical Institute
Organizer(s): Aaditya K Ramdas, Carnegie Mellon University
Chair(s): Aaditya K Ramdas, Carnegie Mellon University
10:05 AM Bringing Betting Games Back to the Center of Probability and Statistics
Glenn Shafer , Rutgers University
10:30 AM Representing e-values using convex duality
Martin Larsson, Carnegie Mellon University
10:55 AM Valid sequential inference on probability forecast performance
Johanna Ziegel, University of Bern
11:20 AM Multiple Hypothesis Testing with E-Values Versus P-Values
Ruodu Wang, University of Waterloo
11:45 AM Floor Discussion
 
 

79 ! 		Mon, 8/9/2021, 10:00 AM - 11:50 AM Virtual
Measure Transportation-Based Statistical Inference — Topic-Contributed Papers
IMS, Section on Nonparametric Statistics, Section on Statistical Learning and Data Science
Organizer(s): Fang Han, University of Washington
Chair(s): Fang Han, University of Washington
10:05 AM Fully Distribution-Free Center-Outward Rank Tests for Multiple-Output Regression and MANOVA Presentation
Marc Hallin, Université libre de Bruxelles
10:25 AM Distribution-Free Consistent Independence Tests via Center-Outward Ranks and Signs
Mathias Drton, Technical University of Munich; Marc Hallin, Université libre de Bruxelles; Fang Han, University of Washington; Hongjian Shi, University of Washington
10:45 AM From Smooth Wasserstein Distance to Dual Sobolev Norm: Empirical Approximation and Statistical Applications
Kengo Kato, Cornell University; Ziv Goldfeld, Cornell University; Sloan Nietert, Cornell University
11:05 AM Optimal Transport for Fairness in Machine Learning
jean michel loubes, University of Toulouse
11:25 AM Consistent Estimation of Optimal Transport Plans
Johan Segers, UCLouvain
11:45 AM Floor Discussion
 
 

113 		Mon, 8/9/2021, 1:30 PM - 3:20 PM Virtual
Nonlinear and Nonstationary Dependent Processes: Modeling, Inference, and Applications — Invited Papers
Business and Economic Statistics Section, IMS, International Indian Statistical Association
Organizer(s): Soumendra Lahiri, Washington University
Chair(s): Soutir Bandyopadhyay, Colorado School of Mines
1:35 PM Inference and Prediction for Quadratic Processes
Tucker Sprague McElroy, US Census Bureau; Dhrubajyoti Ghosh, Washington University; Soumendra Lahiri, Washington University
2:00 PM Polyspectral Mean Estimation of General Nonlinear Processes Presentation
Dhrubajyoti Ghosh, Washington University; Tucker Sprague McElroy, US Census Bureau; Soumendra Lahiri, Washington University
2:25 PM A Bayesian Framework for Modeling Outliers in Time Series in Post COVID-19 Era
Anindya Roy, U.S. Census Bureau/ UMBC; Tucker Sprague McElroy, US Census Bureau
2:50 PM Locally Stationary Spatial Processes
Soumendra Lahiri, Washington University; Tucker Sprague McElroy, US Census Bureau; Daniel Census Weinberg, US Census Bureau
3:15 PM Floor Discussion
 
 

114 		Mon, 8/9/2021, 1:30 PM - 3:20 PM Virtual
Medallion Lecture I — Invited Papers
IMS
Organizer(s): Bodhisattva Sen, Columbia University
Chair(s): Bodhisattva Sen, Columbia University
1:35 PM Statistical Optimal Transport
Philippe Rigollet, MIT
3:15 PM Floor Discussion
 
 

115 		Mon, 8/9/2021, 1:30 PM - 3:20 PM Virtual
New Researchers Group Session — Invited Papers
IMS
Organizer(s): James Johndrow, University of Pennsylvania; Alexander Volfovsky, Duke University
Chair(s): James Johndrow, University of Pennsylvania
1:35 PM The Barker Proposal: Combining Robustness and Efficiency in Gradient-Based MCMC
Giacomo Zanella, Bocconi University
2:00 PM Efficient Bernoulli Factory MCMC for Intractable Posteriors
Dootika Vats, Indian Institute of Technology, Kanpur
2:25 PM A Framework for Adaptive MCMC Targeting Multimodal Distributions
Emilia Pompe, University of Oxford
2:50 PM Schrödinger Bridge Samplers
Espen Bernton, Columbia University
3:15 PM Floor Discussion
 
 

117 		Mon, 8/9/2021, 1:30 PM - 3:20 PM Virtual
Xiangrong Yin Memorial Session — Invited Panel
Memorial, IMS, Section on Nonparametric Statistics, History of Statistics Interest Group
Organizer(s): Jiaying Weng, Bentley University
Chair(s): Qin Wang, University of Alabama
1:35 PM Xiangrong Yin Memorial Session
Panelists: Dennis Cook, University of Minnesota
John Stufken, UNC Greensboro
Bing Li, Penn State University
Arnold Stromberg, University of Kentucky
Solomon Harrar, University of Kentucky
3:10 PM Floor Discussion
 
 

120 ! 		Mon, 8/9/2021, 1:30 PM - 3:20 PM Virtual
Challenges and Recent Advances in Private Data Analysis — Topic-Contributed Papers
Section on Nonparametric Statistics, IMS, CHANCE, Section on Statistical Learning and Data Science
Organizer(s): Linjun Zhang, Rutgers University
Chair(s): Linjun Zhang, Rutgers University
1:35 PM The Cost of Privacy in Generalized Linear Models: Algorithms and Minimax Lower Bounds
Yichen Wang, University of Pennsylvania; Tony Cai, University of Pennsylvania; Linjun Zhang, Rutgers University
1:55 PM Differentially Private Statistics for Collaborative Neuroinformatics
Anand Sarwate, Rutgers University
2:15 PM Interactive Versus Non-Interactive Locally Differentially Private Estimation: Two Elbows for the Quadratic Functional
Lukas Steinberger, University of Vienna
2:35 PM A Central Limit Theorem and Uncertainty Principle for Differentially Private Query Answering Presentation
Jinshuo Dong, Northwestern University
2:55 PM High-Dimensional, Differentially-Private EM Algorithm: Methods and Near Optimal Statistical Guarantees
Zhe Zhang, Rutgers University, New Brunswick; Linjun Zhang, Rutgers University
3:15 PM Floor Discussion
 
 

137 		Mon, 8/9/2021, 5:15 PM - 6:45 PM Virtual
IMS Presidential Address — Invited Papers
IMS
Organizer(s): Bodhisattva Sen, Columbia University
Chair(s): Xiao-Li Meng, Harvard University
5:20 PM Proactive and All-Encompassing Statistics
Regina Liu, Rutgers University
9:15 PM Floor Discussion
 
 

140 * ! 		Tue, 8/10/2021, 10:00 AM - 11:50 AM Virtual
Change-Points in Multivariate and High-Dimensional Data — Invited Papers
Section on Nonparametric Statistics, IMS, Section on Statistical Learning and Data Science
Organizer(s): Piotr Fryzlewicz, London School of Economics
Chair(s): Qiwei Yao, London School of Economics and Political Science
10:05 AM Inference for a Change Point in High-Dimensional Data via Self-Normalization
Runmin Wang, Southern Methodist University; Changbo Zhu, University of California, Davis; Stanislav Volgushev, University of Toronto; Xiaofeng Shao, University of Illinois at Urbana-Champaign
10:25 AM Jump or Kink: Super-Efficiency in Segmented Linear Regression Break-Point Estimation
Yining Chen, London School of Economics
10:45 AM Change-Point Detection for Multivariate and Non-Euclidean Data with Local Dependency
Hao Chen, University of California, Davis
11:05 AM Detection and Estimation of Signals in Space-Time Fields
David Siegmund, Stanford University
11:25 AM Discussant: Piotr Fryzlewicz, London School of Economics
11:40 AM Floor Discussion
 
 

143 * ! 		Tue, 8/10/2021, 10:00 AM - 11:50 AM Virtual
New Machine Learning Tools for Mobile Health Data and Individual Intervention — Invited Papers
Lifetime Data Science Section, Section on Statistical Learning and Data Science, IMS, ENAR
Organizer(s): Annie Qu, Unviersity of California Irvine
Chair(s): Bin Nan, University of California Irvine
10:05 AM Inference of Causal Relations with Interventions
Chunlin Li, University of Minnesota; Xiaotong T Shen, University of Minnesota; Wei Pan, University of Minnesota
10:30 AM Tracking Weight Loss Before and During Pregnancy
Heping Zhang, Yale University
10:55 AM Efficient Learning of Optimal Individualized Treatment Rules
Weibin Mo, University of North Carolina; Yufeng Liu, University of North Carolina at Chapel Hill
11:20 AM Supervised Learning of Health-Related Secret Codes from Wearable Devices Data
Peter X.K. Song, University of Michigan
11:45 AM Floor Discussion
 
 

145 ! 		Tue, 8/10/2021, 10:00 AM - 11:50 AM Virtual
Trend Filtering and Related Regression Methods — Invited Papers
IMS, International Indian Statistical Association, Section on Nonparametric Statistics
Organizer(s): Sabyasachi Chatterjee, University of Illinois at Urbana-Champaign
Chair(s): Anamitra Chaudhuri, University of Illinois at Urbana-Champaign
10:05 AM Adaptive Online Forecasting of Trends
Yu-Xiang Wang, UC Santa Barbara
10:30 AM MARS via LASSO
Dohyeong Ki; Billy Fang, Google; Adityanand Guntuboyina, UC Berkeley
10:55 AM Adaptive Risk Bounds for Quantile Trend Filtering
Oscar Madrid Padilla, University of California, Los Angeles
11:20 AM Dyadic CART Revisited
Sabyasachi Chatterjee, University of Illinois at Urbana-Champaign
11:45 AM Floor Discussion
 
 

153 * ! 		Tue, 8/10/2021, 10:00 AM - 11:50 AM Virtual
Statistics in the Public Sphere — Invited Papers
IMS
Organizer(s): Alexandra Chouldechova, Carnegie Mellon University
Chair(s): Alexandra Chouldechova, Carnegie Mellon University
10:05 AM Data, algorithms and data governance
Sofia Olhede, EPFL SB Math SDS
10:30 AM How to mislead with statistics: Lessons from recent attempts to subvert the US election with data analysis
Kristian Lum, Twitter
10:55 AM One Person, One Vote
Sharad Goel, Harvard University
11:20 AM The Data-driven Policy Researcher: what/how/why?
Osonde Osoba, RAND
11:45 AM Floor Discussion
 
 

184 ! 		Tue, 8/10/2021, 1:30 PM - 3:20 PM Virtual
Recent Advances in Statistical Machine Learning — Invited Papers
IMS, Section on Statistical Learning and Data Science, Section on Nonparametric Statistics
Organizer(s): Jianqing Fan , Princeton University
Chair(s): Jianqing Fan , Princeton University
1:35 PM Inhomogeneous-Word PCA for Estimating the Weights in a Topic Model
Tracy Ke, Harvard University; Minzhe Wang, University of Chicago
2:00 PM Provable Boolean Interaction Recovery from Tree Structures Obtained via Random Forests
Bin Yu, University of California, Berkeley; Merle Behr, UC Berkeley; Yu Wang, University of California, Berkeley; Xiao Li, University of California, Berkeley
2:25 PM High-Dimensional Principle Component Analysis with Heterogeneous Missingness
Ziwei Zhu , University of Michigan, Ann Arbor; Tengyao Wang, University College London; Richard J. Samworth, University of Cambridge
2:50 PM Fast Network Community Detection with Profile-Pseudo Likelihood Methods
Ji Zhu, University of Michigan
3:15 PM Floor Discussion
 
 

193 		Tue, 8/10/2021, 1:30 PM - 3:20 PM Virtual
Medallion Lecture II — Invited Papers
IMS
Organizer(s): Bodhisattva Sen, Columbia University
Chair(s): Florentina Bunea, Cornell University
1:35 PM What Kinds of Functions Do Neural Networks Learn? Presentation
Robert Nowak, University of Wisconsin-Madison
3:15 PM Floor Discussion
 
 

213 		Tue, 8/10/2021, 3:30 PM - 5:00 PM Virtual
Wald Lecture I — Invited Papers
IMS
Organizer(s): Bodhisattva Sen, Columbia University
Chair(s): Bin Yu, University of California, Berkeley
3:35 PM Modeling and Estimating Large Sparse Networks: Wald Lectures I and II
Jennifer Chayes, University of California, Berkeley
 
 

220 ! 		Wed, 8/11/2021, 10:00 AM - 11:50 AM Virtual
High-Dimensional Analysis of Complex Dependent Data — Invited Papers
Business and Economic Statistics Section, IMS, Royal Statistical Society
Organizer(s): Anindya Roy, U.S. Census Bureau/ UMBC
Chair(s): Anindya Roy, U.S. Census Bureau/ UMBC
10:05 AM Sparse Identification and Estimation of Large-Scale Vector AutoRegressive Moving Averages
Sumanta Basu, Cornell University
10:30 AM Sequential Change-Point Detection in High-Dimensional Gaussian Graphical Models
George Michailidis, U Florida
10:55 AM High-Dimensional Spectral Analysis
Efstathios Paparoditis, University of Cyprus; Jonas Krampe, University of Mannheim
11:20 AM High-Dimensional Analysis of Complex Dependent Data
Anders Kock, University of Oxford
11:45 AM Floor Discussion
 
 

221 		Wed, 8/11/2021, 10:00 AM - 11:50 AM Virtual
Topics on Deep Learning — Invited Papers
IMS, Section on Statistical Learning and Data Science
Organizer(s): Xiaotong T Shen, University of Minnesota
Chair(s): Fei Xue, University of Pennsylvania
10:05 AM Overparametrization in Linear Models, and the Uniform Consistency of Cross-Validation for Ridge Regression
Pratik Patil, Carnegie Mellon University; Ryan Tibshirani, Carnegie Mellon University; Yuting Wei, Carnegie Mellon University; Alessandro Rinaldo, Carnegie Mellon University
10:35 AM Significance Tests for Feature Relevance of a Black-Box Learner
Ben Dai, University of Minnesota; Xiaotong T Shen, University of Minnesota; Wei Pan, University of Minnesota
11:05 AM What Causes the Test Error? Going Beyond Bias-Variance via ANOVA
Edgar Dobriban, University of Pennsylvania
11:35 AM Floor Discussion
 
 

223 * ! 		Wed, 8/11/2021, 10:00 AM - 11:50 AM Virtual
Recent Developments in Differential Privacy — Invited Papers
Section on Statistical Learning and Data Science, IMS, Section on Nonparametric Statistics
Organizer(s): Xuan Bi, University of Minnesota
Chair(s): Xuan Bi, University of Minnesota
10:05 AM Differential Private Data Release Using Latent Factor Model Transform
Annie Qu, Unviersity of California Irvine; Yanqing Zhang, Yunnan University; Niansheng Tang, Yunnan U
10:30 AM Private Posterior Inference Consistent with Public Information
Aleksandra Slavkovic, Penn State University
10:55 AM Congenial Differential Privacy Under Mandated Disclosure
Ruobin Gong, Rutgers University; Xiao-Li Meng, Harvard University
11:20 AM Near Instance-Optimality in Differential Privacy
John C Duchi, Stanford University; Hilal Asi, Stanford University
11:45 AM Floor Discussion
 
 

225 * ! 		Wed, 8/11/2021, 10:00 AM - 11:50 AM Virtual
Recent Advances in Bayesian Methods for Complex Data Structures — Invited Papers
Section on Bayesian Statistical Science, International Society for Bayesian Analysis (ISBA), IMS
Organizer(s): Garritt L Page, Brigham Young University
Chair(s): Garritt L Page, Brigham Young University
10:05 AM Seemingly Unrelated Multi-State Processes: A Bayesian Nonparametric Approach
Maria De Iorio, University of College London and Yale-NUS College
10:35 AM Optimal Bayesian Estimation of Gaussian Mixtures with Growing Number of Components
Lizhen Lin, The University of Notre Dame; Ilsang Ohn, The University of Notre Dame
11:05 AM Grid-Uniform Copulas and Rectangle Exchanges: Model and Bayesian Inference for a Rich Class of Copula Functions
Alejandro Jara, Pontificia Universidad Católica de Chile
11:35 AM Floor Discussion
 
 

227 * ! 		Wed, 8/11/2021, 10:00 AM - 11:50 AM Virtual
The Best of Annals of Applied Statistics — Invited Papers
IMS, Caucus for Women in Statistics
Organizer(s): Karen Kafadar, University of Virginia
Chair(s): Karen Kafadar, University of Virginia
10:05 AM Late 19th-Century Navigational Uncertainties and Their Influence on Sea Surface Temperature Estimates
Chenguang Dai, Harvard University; Duo Chan, Harvard University; Peter Huybers, Harvard University; Natesh Pillai, Harvard University
10:35 AM Statistical Methods for Replicability Assessment Presentation
Kenneth Hung, Core Data Science, Facebook; William Fithian, University of California, Berkeley
11:05 AM A Bayesian Model of Microbiome Data for Simultaneous Identification of Covariate Associations and Prediction of Phenotypic Outcomes
Matthew David Koslovsky, Colorado State University; Marina Vannucci, Rice
11:35 AM Floor Discussion
 
 

228 		Wed, 8/11/2021, 10:00 AM - 11:50 AM Virtual
IMS Lawrence D. Brown PhD Student Award Session — Invited Papers
IMS
Organizer(s): Bodhisattva Sen, Columbia University
Chair(s): Tracy Ke, Harvard University
10:05 AM First-Order Newton-Type Estimator for Distributed Estimation and Inference
Yichen Zhang, Purdue University; Xi Chen, NYU; Weidong Liu, Shanghai Jiao Tong University
10:35 AM Minimax Optimality of Permutation Tests
Ilmun Kim, The University of Cambridge; Sivaraman Balakrishnan, Carnegie Mellon University; Larry Wasserman, Carnegie Mellon University
11:05 AM Inference in Interpretable Latent Factor Regression Models Presentation
Xin Bing, Cornell University
11:35 AM Floor Discussion
 
 

259 		Wed, 8/11/2021, 1:30 PM - 3:20 PM Virtual
Recent Developments in Statistical Inference Using Distance Correlation and Related Dependence Metrics — Invited Papers
Section on Nonparametric Statistics, International Chinese Statistical Association, IMS
Organizer(s): Xiaofeng Shao, University of Illinois at Urbana-Champaign
Chair(s): Changbo Zhu, University of California, Davis
1:35 PM High-Dimensional Change-Point Detection Using Generalized Homogeneity Metrics Presentation
Xianyang Zhang, Texas A&M University; Shubhadeep Chakraborty, University of Washington
2:05 PM Asymptotic Distributions of High-Dimensional Distance Correlation Inference
Jinchi Lv, University of Southern California
2:35 PM Concentration Inequality for Distance Covariances and Applications in Feature Screening
Xiaoming Huo, Georgia Institute of Technology
3:05 PM Floor Discussion
 
 

264 ! 		Wed, 8/11/2021, 1:30 PM - 3:20 PM Virtual
Frontiers of High-Dimensional Statistics — Invited Papers
IMS, Text Analysis Interest Group
Organizer(s): Pragya Sur, Harvard University
Chair(s): Zhou Fan, Yale University
1:35 PM New Estimates of the Wasserstein Distance Between Document-Generating Distributions in Topic Models
Florentina Bunea, Cornell University
2:00 PM Risk Estimation Under High-Dimensional Asymptotics
Arian Maleki, Columbia University; Kamiar Rahnamad rad, City University of New York; Wenda Zhou, Flat iron institute
2:25 PM Second-Order Stein: SURE for SURE and Other Applications
Cun-Hui Zhang, Rutgers University
2:50 PM Discussant: Pragya Sur, Harvard University
3:15 PM Floor Discussion
 
 

265 ! 		Wed, 8/11/2021, 1:30 PM - 3:20 PM Virtual
Recent Advances in Statistical Network Analysis — Invited Papers
International Indian Statistical Association, IMS, Section on Statistical Learning and Data Science
Organizer(s): Sumit Mukherjee, Columbia University
Chair(s): Sumit Mukherjee, Columbia University
1:35 PM Accounting for Network Noise: Counting, Experimenting, and Epidemic Control
Eric Kolaczyk, Boston University
2:05 PM Long-Range Dependence in Evolving Network Models
Shankar Bhamidi, University of North Carolina
2:35 PM Motif Estimation via Subgraph Sampling: The Fourth-Moment Phenomenon
Bhaswar Bikram Bhattacharya, Department of Statistics, University of Pennsylvania; Sayan Das, Departments of Mathematics, Columbia University; Sumit Mukherjee, Columbia University
3:05 PM Floor Discussion
 
 

270 		Wed, 8/11/2021, 1:30 PM - 3:20 PM Virtual
Medallion Lecture IV — Invited Papers
IMS
Organizer(s): Bodhisattva Sen, Columbia University
Chair(s): Victor Michael Panaretos, EPFL
1:35 PM Empirical Optimal Transport: Inference, Algorithms, Applications Presentation
Axel Munk, University of Göttingen
3:15 PM Floor Discussion
 
 

276 		Wed, 8/11/2021, 1:30 PM - 3:20 PM Virtual
Statistical Foundations of Reinforcement Learning — Topic-Contributed Papers
IMS, Section on Statistical Learning and Data Science, International Chinese Statistical Association
Organizer(s): Yuxin Chen, Princeton University
Chair(s): Yuxin Chen, Princeton University
1:35 PM Breaking the sample size barrier in model-based reinforcement learning
Yuting Wei, Carnegie Mellon University
1:55 PM Distributional Robust Batch Contextual Bandits
Zhengyuan Zhou, New York University
2:15 PM Learning Good State and Action Representations via Tensor Decomposition
Anru Zhang, University of Wisconsin-Madison; Chengzhuo Ni, Princeton University; Yaqi Duan, Princeton University; Mengdi Wang, Princeton University
2:35 PM Dynamic Batch Learning in High-Dimensional Sparse Linear Contextual Bandits
Zhimei Ren, Stanford University; Zhengyuan Zhou, New York University
2:55 PM Is Q-Learning Minimax Optimal?
Yuejie Chi, Carnegie Mellon University
3:15 PM Floor Discussion
 
 

289 		Wed, 8/11/2021, 1:30 PM - 3:20 PM Virtual
Recent Advances in Mathematical Statistics and Probability — Contributed Speed
IMS
Chair(s): Pierre C Bellec, Rutgers University
1:35 PM Multistage Estimators for Missing Covariates and Incomplete Outcomes
Daniel Suen, University of Washington; Yen-Chi Chen, University of Washington
1:40 PM Adversarial Contamination of Networks: A New Trimming Method
Sheyda Peyman, University of Maryland; Vince Lyzinski, University of Maryland
1:45 PM Subgraph Nomination: Query by Example Subgraph Retrieval in Networks
AlFahad AlQadhi, University of Maryland; Carey E Priebe, Johns Hopkins University; Hayden S. Helm, Johns Hopkins University; Vince Lyzinski, University of Maryland
1:50 PM Random Graph Asymptotics for Treatment Effect Estimation Under Network Interference
Shuangning Li, Stanford University; Stefan Wager, Stanford University
1:55 PM Density Estimation in the Context of Deconvolution
Sucharita Ghosh, Swiss Federal Research Institute WSL
2:00 PM Two Symmetric and Computationally Efficient Gini Correlations
Courtney Vanderford, University of Mississippi; Xin Dang, University of Mississippi; Yongli Sang, University of Louisiana at Lafayette
2:05 PM WITHDRAWN: Hierarchical Bayesian Analysis of Organ Weight Toxicity Data Across Multiple Rodent Studies
GARY LARSON, DLH CORPORATION; Jeffrey Krause, DLH CORPORATION; Guanhua Xie, DLH CORPORATION; Shawn Harris, DLH CORPORATION; Sandra McBride, DLH CORPORATION; Keith Shockley, National Institute of Environmental Health Sciences
2:10 PM Polluted threshold growth models in Two Dimensions with a General Neighborhood Structure
Amartya Ghosh, The Ohio State University
2:15 PM Copula-Based Sensitivity Analysis for Causal Inference with Unobserved Confounding
Jiajing Zheng, University of California, Santa Barbara; Alexander D’Amour, Google Brain; Alexander Franks, University of California, Santa Barbara
2:20 PM Utilizing Wasserstein Distance in Convergence Complexity Analysis of MCMC Algorithms
Bryant Frost Davis, University of Florida; James P Hobert, University of Florida
2:30 PM Approximate Cosufficient Sampling for Goodness-of-Fit Tests and Synthetic Data
Jordan Alexander Awan, Purdue University; Zhanrui Cai, The Pennsylvania State University
2:35 PM Estimating Drift and Minorization Coefficients for Gibbs Sampling Algorithms
David Spade, University of Wisconsin--Milwaukee
2:40 PM Kernel Smoothing, Mean Shift, and Their Learning Theory with Directional Data
Yikun Zhang, University of Washington, Seattle; Yen-Chi Chen, University of Washington
2:45 PM Simultaneous confidence bands for comparing variance functions of two samples in nonparametric regression model
Chen Zhong, Tsinghua University; Lijian Yang, Tsinghua University
2:50 PM Inference for Linear Functional in High-Dimensional Quantile Regression
Prabrisha Rakshit, Rutgers, The State University of New Jersey; Zijian Guo, Rutgers University
2:55 PM Functional Sufficient Dimension Reduction Through Average Fréchet Derivatives
Kuang-Yao Lee, Temple University; Lexin Li, University of California, Berkeley
3:00 PM Estimate Low-Rank Matrices via Approximate Message Passing with Spectral Initialization
Xinyi Zhong, Yale University; Tianhao Wang, Yale University ; Zhou Fan, Yale University
3:05 PM Evaluating More Moments of a Unit-Root Test in Elementary Models
Ray-Shine Lee, Shine-In Quantitative Research E-Commerce Company
3:10 PM Combinatorial Regression Model in Abstract Simplicial Complexes
Andrej Srakar, Institute for Economic Research (IER) and University of Ljubljana
 
 

293 ! 		Wed, 8/11/2021, 3:30 PM - 5:20 PM Virtual
Causality for Complex Data — Invited Papers
IMS
Organizer(s): Jonas Peters, University of Copenhagen
Chair(s): Jonas Peters, University of Copenhagen
3:35 PM Benefiting from Causal Structure: Using Stability for Inference in Complex Data
Niklas Pfister, University of Copenhagen
4:00 PM Causal Inference on Distribution Functions
Linbo Wang, University of Toronto
4:25 PM Social Network Dependence and Unmeasured Confounding
Elizabeth L. Ogburn, Johns Hopkins University
4:50 PM Assessing Causal Inference Using Adaptively Collected Data
Susan Murphy, Harvard University
5:15 PM Floor Discussion
 
 

296 		Wed, 8/11/2021, 3:30 PM - 5:20 PM Virtual
Statistical Inference with Permuted Data — Invited Papers
IMS
Organizer(s): Jonathan Niles-Weed, New York University
Chair(s): Jonathan Niles-Weed, New York University
3:35 PM Community Detection in Multi-Layer Networks
Zongming Ma, University of Pennsylvania; Shuxiao Chen, University of Pennsylvania; Sifan A. Liu, Stanford University
4:00 PM Adaptive Estimation in Nonparametric Bradley-Terry Model Presentation
Sumit Mukherjee, Columbia University; Sabyasachi Chatterjee, University of Illinois at Urbana-Champaign
4:25 PM Ranking from Pairwise Comparisons: The Role of the Underlying Probabilistic Model
Shivani Agarwal, University of Pennsylvania
4:50 PM Miscalibration in Human Evaluations Presentation
Nihar Shah, Carnegie Mellon University
5:15 PM Floor Discussion
 
 

313 * ! 		Wed, 8/11/2021, 3:30 PM - 5:20 PM Virtual
Recent Advances in Symbolic Data Analysis — Topic-Contributed Papers
Section on Statistical Learning and Data Science, Section on Statistical Computing, IMS
Organizer(s): S. Yaser Samadi, Southern Illinois University Carbondale
Chair(s): Jenifer Le-Rademacher , Department of Health Sciences Research, Mayo Clinic
3:35 PM Partitioning Interval-Valued Data Using Regression
Lynne Billard, University of Georgia; Fei Liu, Bank of America
3:55 PM Facial Recognition Development Using Principal Component Analysis for Interval-Valued Face Data Set
Anuradha Roy, The University of Texas at San Antonio
4:15 PM Symbolic Interval-Valued Time Series: Theory and Applications
S. Yaser Samadi, Southern Illinois University Carbondale; Lynne Billard, University of Georgia
4:35 PM It’s Natural to Think About Cluster Randomized Trials (CRTs) Within the Symbolic Data Framework: The Symbolic Two-Step Method in the Design and Analysis of CRTs
David Zahrieh, Mayo Clinic
4:55 PM Floor Discussion
 
 

328 		Thu, 8/12/2021, 10:00 AM - 11:50 AM Virtual
Advances in MCMC Theory and Practice — Invited Papers
IMS
Organizer(s): Jason Xu, Duke University
Chair(s): Jason Xu, Duke University
10:05 AM Effortless Frequentist Covariances of Posterior Expectations from MCMC
Tamara Broderick, MIT
10:30 AM Repulsive Mixture Modeling Through Matern Processes
Vinayak Rao, Purdue University; Hanxi Sun, Purdue University
10:55 AM Scalable Bayesian Inference for Phylodynamics
Julia A. Palacios, Stanford University; Sifan A. Liu, Stanford University
11:20 AM Exact Convergence Rate Analysis of the Independence Metropolis-Hastings Algorithms Presentation
Guanyang Wang, Rutgers University
11:45 AM Floor Discussion
 
 

329 		Thu, 8/12/2021, 10:00 AM - 11:50 AM Virtual
New Statistical Learning and Methods in Nonparametric Statistics — Invited Papers
Section on Nonparametric Statistics, IMS, General Methodology
Organizer(s): Rui Song, North Carolina State University
Chair(s): Chengchun Shi, LSE
10:05 AM Deep Large-Scale Spatiotemporal Forecasting Methods
Hongtu Zhu, University of North Carolina
10:25 AM Nonparametric Interaction Selection
Yushen Dong, University of Illinois at Chicago; Yichao Wu, University of Illinois at Chicago
10:45 AM Efficient Estimation of Associations Between Multiple Predictors and Survival Outcomes
Ian McKeague, Columbia University
11:05 AM AdaBoost Semiparametric Model Averaging Prediction for Multiple Categories
Jialiang Li, National University of Singapore
11:25 AM Distribution-Free Inference for Regression
Rina Foygel Barber, University of Chicago; Yonghoon Lee, University of Chicago
11:45 AM Floor Discussion
 
 

333 * ! 		Thu, 8/12/2021, 10:00 AM - 11:50 AM Virtual
Recent Developments in Network Inference Methods — Invited Papers
IMS, International Indian Statistical Association, Section on Statistical Learning and Data Science
Organizer(s): Dr. Shirshendu Chatterjee, City University of New York
Chair(s): Dr. Shirshendu Chatterjee, City University of New York
10:05 AM Bootstrap for Networks: From Parametric to Nonparametric Approaches
Liza Levina, University of Michigan
10:30 AM Identifying Heterogeneous Temporal Structure from Multiple Network Time Series
Carey E Priebe, Johns Hopkins University; Guodong Chen, Johns Hopkins University; Jonathan Larson, Microsoft Research; Weiwei Yang, Mocrosoft Research; Christopher White, Microsoft Research; Joshua Vogelstein, Johns Hopkins University; Youngser Park, Johns Hopkins University
10:55 AM Statistical Inference for Networks with Dependent Edges
Sharmodeep Bhattacharyya, Oregon State University; Dr. Shirshendu Chatterjee, City University of New York; Soumendu Sundar Mukherjee, Indian Statistical Institute
11:20 AM Hierarchical stochastic block model for multiplex networks
Arash A. Amini, UCLA
11:45 AM Floor Discussion
 
 

336 		Thu, 8/12/2021, 10:00 AM - 11:50 AM Virtual
Le Cam Lecture — Invited Papers
IMS
Organizer(s): Bodhisattva Sen, Columbia University
Chair(s): Richard J. Samworth, University of Cambridge
10:05 AM Understanding Spectral Embedding
Jianqing Fan , Princeton University
11:45 AM Floor Discussion
 
 

347 ! 		Thu, 8/12/2021, 10:00 AM - 11:50 AM Virtual
Recent Advances in Clustering and Mixture Models Analysis — Topic-Contributed Papers
Section for Statistical Programmers and Analysts, IMS, Section on Statistical Learning and Data Science, International Chinese Statistical Association
Organizer(s): Anderson Ye Zhang, University of Pennsylvania
Chair(s): Anderson Ye Zhang, University of Pennsylvania
10:05 AM Structures of Local Minima in K-Means and the Likelihood of Mixture Models
Yudong Chen, School of ORIE, Cornell University; Xumei Xi, School of ORIE, Cornell University
10:25 AM Causal Inference for Randomized Experiments in Social Networks
David Choi, Carnegie Mellon University
10:45 AM Learning Mixtures of Permutations: Groups of Pairwise Comparisons and Combinatorial Method of Moments Presentation
Cheng Mao, Georgia Institute of Technology; Yihong Wu, Yale
11:05 AM Efficient Clustering for Stretched Mixtures: Landscape and Optimality
Kaizheng Wang, Columbia University; Yuling Yan, Princeton University; Mateo Diaz, Cornell University
11:25 AM Sparse Topic Modeling: Computational Efficiency and Near-Optimal Algorithms
Ruijia Wu, Department of Statistics, University of Pennsylvania; Linjun Zhang, Rutgers University; Tony Cai, University of Pennsylvania
11:45 AM Floor Discussion
 
 

359 * ! 		Thu, 8/12/2021, 12:00 PM - 1:50 PM Virtual
Geometry and Bayes: Better Together — Invited Papers
International Society for Bayesian Analysis (ISBA), IMS, Section on Bayesian Statistical Science, Caucus for Women in Statistics
Organizer(s): Didong Li, Princeton University
Chair(s): Didong Li, Princeton University
12:05 PM Adapting Viral Diffusions to the Geometry of Global Air Transport
Andrew J Holbrook, UCLA Biostatistics
12:35 PM On the Geometry of Bayesian Inference
Garritt L Page, Brigham Young University; Miguel De Carvahlo, University of Edinburgh; Bradley Barney, University of Utah
1:05 PM Diffusion-Based Gaussian Processes on Restricted Domains
David Dunson, Duke University; Hau-Tieng Wu, Duke University; Nan Wu, Duke University
1:35 PM Floor Discussion
 
 

364 * ! 		Thu, 8/12/2021, 12:00 PM - 1:50 PM Virtual
Network Science: Statistical Approaches and Beyond — Invited Papers
WNAR, IMS, JBES-Journal of Business & Economic Statistics
Organizer(s): Rachel Wang, University of Sydney
Chair(s): Purnamrita Sarkar, University of Texas, Austin
12:05 PM Nearly-Optimal Prediction of Missing Links in Networks via Stacking Presentation
Aaron Clauset, University of Colorado Boulder
12:30 PM Scientific Impact of Statistical Theory and Methodology via Citation Network Analysis
Xin Tong, University of Southern California; Lijia Wang, University of Southern California ; Rachel Wang, University of Sydney
12:55 PM Social Learning: Degree-Weighted Updating and Convergence Speed
Yiqing Xing, Johns Hopkins University; Xin Tong, University of Southern California; Xiao Han, University of Science and Technology of China; Yusheng Wu, University of Southern California
1:20 PM Discussant: Peter Bickel, University of California, Berkeley
1:40 PM Floor Discussion
 
 

367 		Thu, 8/12/2021, 12:00 PM - 1:50 PM Virtual
Medallion Lecture III — Invited Papers
IMS
Organizer(s): Bodhisattva Sen, Columbia University
Chair(s): Haiyan Huang, University of California, Berkeley
12:05 PM DNA Copy Number Profiling from Bulk Tissues to Single Cells
Nancy Zhang, The University of Pennsylvania
1:45 PM Floor Discussion
 
 

368 		Thu, 8/12/2021, 12:00 PM - 1:50 PM Virtual
AOS Lecture — Invited Papers
IMS
Organizer(s): Richard J. Samworth, University of Cambridge; Ming Yuan, University of Wisconsin-Madison
Chair(s): Richard J. Samworth, University of Cambridge
12:05 PM Second Order Stein: SURE for SURE and Other Applications in High-Dimensional Inference
Pierre C Bellec, Rutgers University; Cun-Hui Zhang, Rutgers University
12:30 PM One- and Two-Sided Composite-Composite Tests in Gaussian Mixture Models
Alexandra Carpentier, OvGU; Nicolas Verzelen, INRAE; Etienne Roquain, Universite Paris Descartes; Sylvain Delattre, Universite Paris Descartes
12:55 PM Only Closed Testing Procedures Are Admissibility for Controlling False Discovery Proportions
Jelle Goeman, Leiden University Medical Center; Aldo Solari, University of Milano-Bicocca; Jesse Hemerik, Wageningen University & Research
1:20 PM Optimal Rates of Entropy Estimation Over Lipschitz Balls
Yihong Wu, Yale
1:45 PM Floor Discussion
 
 

373 * ! 		Thu, 8/12/2021, 12:00 PM - 1:50 PM Virtual
Analysis of Duration Data, with Applications to the COVID-19 Pandemic — Topic-Contributed Papers
IMS, Biometrics Section, Biopharmaceutical Section
Organizer(s): Piet Groeneboom, Delft University
Chair(s): Geurt Jongbloed, Delft Institute of Applied Mathematics
12:05 PM The Generation Time Distribution: Problems with Estimating It and Consequences Thereof
Tom Britton, Stockholm University
12:25 PM Estimating the Generation Time and Relative Infectiousness from Contact Tracing Data
Hiroshi Nishiura, Kyoto University School of Public Health
12:45 PM Estimation of Incubation Time and Latency Time Distribution of SARS-CoV-2 Presentation
Ronald Geskus, Oxford University Clinical Research Unit
1:05 PM Estimation in the singly and doubly interval censored model Presentation
Piet Groeneboom, Delft University
1:25 PM Floor Discussion
 
 

388 * ! 		Thu, 8/12/2021, 2:00 PM - 3:50 PM Virtual
New Development of Change-Point Methods — Invited Papers
IMS, International Chinese Statistical Association, Business and Economic Statistics Section
Organizer(s): Jialiang Li, National University of Singapore
Chair(s): Jialiang Li, National University of Singapore
2:05 PM High-Dimensional, Multiscale Online Changepoint Detection
Tengyao Wang, University College London; Yudong J Chen, University of Cambridge; Richard J. Samworth, University of Cambridge
2:25 PM Monitoring for a Change Point in a Sequence of Distributions
Piotr Kokoszka, Colorado State University ; Lajos Horvath , University of Utah ; Shixuan Wang , University of Reading
2:45 PM L_1 Based Change-Plane Estimation in High Dimensions
Moulinath Banerjee, University of Michigan; Debarghya Mukherjee, University of MIchigan; Ya'acov Ritov, University of Michigan
3:05 PM Simultaneous Detection of Multiple Change Points and Community Structures in Time Series of Networks
Alexander Aue, University of California Davis
3:25 PM On Functional Processes with Multiple Thresholds
Jialiang Li, National University of Singapore; Yaguang Li, University of Toronto; Tailen Hsing, University of Michigan
3:45 PM Floor Discussion
 
 

392 ! 		Thu, 8/12/2021, 2:00 PM - 3:50 PM Virtual
Recent Advances in Tensor Learning — Invited Papers
IMS, International Chinese Statistical Association, Section on Statistical Learning and Data Science
Organizer(s): Will Wei Sun, Purdue University
Chair(s): Will Wei Sun, Purdue University
2:05 PM Improving Sales Forecasting Accuracy: A Tensor Factorization Approach with Demand Awareness Presentation
Xuan Bi, University of Minnesota; Gediminas Adomavicius, University of Minnesota; William Li, Shanghai Jiao Tong University; Annie Qu, Unviersity of California Irvine
2:30 PM Community Detection on Mixture Multi-Layer Networks via Regularized Tensor Decomposition
Dong XIA, Hong Kong University of Science and Technology
2:55 PM Frequentist Predictions with Incorrect Tensor Models
Peter Hoff, Duke University
3:20 PM Dynamic Tensor Factor Model Based on CP Decomposition
Yuefeng Han, Rutgers University; Rong Chen, Rutgers University; Cun-Hui Zhang, Rutgers University
3:45 PM Floor Discussion
 
 

396 ! 		Thu, 8/12/2021, 2:00 PM - 3:50 PM Virtual
Distributional Robustness, Validity, Causality, and Generalizability — Invited Papers
IMS
Organizer(s): Hongseok Namkoong, Columbia University
Chair(s): John C Duchi, Stanford University
2:05 PM Causality and Distribution Generalization
Jonas Peters, University of Copenhagen; Rune Christiansen, University of Copenhagen; Niklas Pfister, University of Copenhagen; Martin Jakobsen, University of Copenhagen; Nicola Gnecco, University of Geneva
2:25 PM Increase Sample Heterogeneity to Improve the Robustness of Causal Effect Estimates
Elizabeth Tipton, Northwestern University
2:45 PM Analyzing the external validity of causal findings against subpopulation shifts
Hongseok Namkoong, Columbia University
3:05 PM Remedying Estimation Unobservability via Distributionally Robust Optimization
Henry Lam, Columbia
3:25 PM Measuring Robustness to Natural Distribution Shifts in Image Classification
Ludwig Schmidt, UC Berkeley
3:45 PM Floor Discussion
 
 

400 ! 		Thu, 8/12/2021, 2:00 PM - 3:50 PM Virtual
Breiman Award Lectures — Invited Papers
Section on Statistical Learning and Data Science, IMS, International Chinese Statistical Association
Organizer(s): Hao Helen Zhang, University of Arizona
Chair(s): Jelena Bradic, University of California, San Diego
2:05 PM Hypothesis Testing After Hypothesis Generation
Daniela Witten, University of Washington; Jacob Bien, University of Southern California; Lucy Gao, University of Waterloo; Anna Neufeld, University of Washington
2:35 PM Some Comments on CV
Trevor JOHN Hastie, STANFORD UNIVERSITY; Stephen Bates, UC Berkeley; Robert Tibshirani, Stanford Univ
3:45 PM Floor Discussion
 
 

402 ! 		Thu, 8/12/2021, 2:00 PM - 3:50 PM Virtual
Integrative Inference with Data from Multiple Sources: Challenges and New Developments — Topic-Contributed Papers
ENAR, IMS, Section on Statistical Computing
Organizer(s): Emily C Hector, North Carolina State University
Chair(s): Emily C Hector, North Carolina State University
2:05 PM Integrating Multisource Block-Wise Missing Data in Model Selection
Fei Xue, University of Pennsylvania; Annie Qu, Unviersity of California Irvine
2:25 PM Integrative Factor Regression and Its Inference for Multimodal Data Analysis
Quefeng Li, University of North Carolina at Chapel Hill; Lexin Li, University of California, Berkeley
2:45 PM Federated Learning Approaches for Integrative Analysis of Heterogeneous Data Sources
Lu Tang, University of Pittsburgh
3:05 PM Data Integration with Oracle Use of External Information from Heterogeneous Populations
Peisong Han, University of Michigan
3:25 PM Causal Inference for Combining RCTs and Observational Studies: Methods Comparison and Medical Application Presentation
Bénédicte Colnet, INRIA Saclay; Imke Mayer, Centre d'Analyse et de Mathématiques Sociales, EHESS; Guanhua Chen, Department of Biostatistics and Medical Informatics, University of Winsconsin-Madison; Awa Dieng, Google Research; Ruohong Li, Indiana University School of Medicine; Gaël Varoquaux, INRIA Saclay; Jean-Philippe Vert, Google Research; Julie Josse, INRIA Sophia-Antipolis; Shu Yang, North Carolina State University
3:45 PM Floor Discussion
 
 

419 * ! 		Thu, 8/12/2021, 4:00 PM - 5:50 PM Virtual
Quantifying the Anthropogenic Fingerprint in Climate Change — Invited Papers
Section on Statistics and the Environment, IMS, Section on Nonparametric Statistics
Organizer(s): Jan Beran, University of Konstanz
Chair(s): Sucharita Ghosh, Swiss Federal Research Institute WSL
4:05 PM A Combined Estimate of Global Temperature Time Series and a Comparison to Climate Models
Peter Craigmile, The Ohio State University; Peter Guttorp, University of Washington and Norwegian Computing Center
4:30 PM Changing Seasons and Related Topics
Jan Beran, University of Konstanz; Britta Steffens, University of Konstanz; Sucharita Ghosh, Swiss Federal Research Institute WSL
4:55 PM What Drives Temperature Anomalies? A Functional SVAR Approach Presentation
J. Isaac Miller, University of Missouri; Yoosoon Chang, Indiana University; Joon Y. Park, Indiana University
5:20 PM Multivariate Integer-Valued Time Series with Flexible Autocovariances and Their Application to Major Hurricane Counts
Vladas Pipiras, University of North Carolina at Chapel Hill
5:45 PM Floor Discussion
 
 

424 		Thu, 8/12/2021, 4:00 PM - 5:50 PM Virtual
Inference in Infectious Diseases — Invited Papers
IMS, International Society for Bayesian Analysis (ISBA), JASA Applications and Case Studies
Organizer(s): Julia A. Palacios, Stanford University
Chair(s): Julia A. Palacios, Stanford University
4:05 PM Bayesian Estimation of the Impacts of Widespread Social Distancing and Other Interventions for COVID-19
Carolin Colijn, Simon Fraser University
4:30 PM Adaptive Preferential Sampling in Phylodynamics
Lorenzo Cappello, Stanford University
4:55 PM Using Multiple Data Streams to Estimate and Forecast SARS-CoV-2 Transmission Dynamics
Vladimir N. Minin, University of California, Irvine
5:20 PM Likelihood-Based Inference for Partially Observed Epidemics via Data Augmentation
Jason Xu, Duke University
5:45 PM Floor Discussion
 
 

425 * ! 		Thu, 8/12/2021, 4:00 PM - 5:50 PM Virtual
Modern Statistical Learning of Complex Data — Invited Papers
Section on Nonparametric Statistics, IMS, Section on Statistical Learning and Data Science
Organizer(s): Lily Wang, Iowa State University
Chair(s): Lily Wang, Iowa State University
4:05 PM Sparse Modeling of Functional Linear Regression via Fused Lasso with Application to Genotype-by-Environment Interaction Studies
Shan Yu, University of Virginia; Lily Wang, Iowa State University; Dan Nettleton, Iowa State University; Aaron Kusmec, Iowa State University
4:25 PM Group Testing with Missing Values
Aurore Delaigle, University of Melbourne; Ruoxu Tan, University of Melbourne
4:45 PM Kernel-Based Learning for Informative Selection in Complex Surveys
Jay Breidt, Colorado State University; Teng Liu, Colorado State University
5:05 PM Robust Estimation of Additive Boundaries with Quantile Regression and Shape Constraints
Lan Xue, Oregon State University; Yan Fang, Shanghai University of International Business and Economics; Carlos Martins-Filho, University of Colorado; Lijian Yang, Tsinghua University
5:25 PM On Function-On-Scalar Quantile Regression
Yusha Liu , University of Chicago; Meng Li, Rice University; Jeffrey S. Morris, University of Pennsylvania Perelman School of Medicine
5:45 PM Floor Discussion
 
 

426 		Thu, 8/12/2021, 4:00 PM - 5:50 PM Virtual
Statistical Optimal Transport — Invited Papers
IMS
Organizer(s): Victor Michael Panaretos, EPFL
Chair(s): Philippe Rigollet, MIT
4:05 PM Sharp Convergence Rates for Empirical Optimal Transport with Smooth Costs
Jonathan Niles-Weed, New York University; Tudor Manole, Carnegie Mellon University
4:45 PM Probabilistic Approximations to Discrete Optimal Transport
Yoav Zemel, University of Cambridge
5:25 PM Discussant: Axel Munk, University of Göttingen
5:45 PM Floor Discussion
 
 

429 		Thu, 8/12/2021, 4:00 PM - 5:50 PM Virtual
Wald Lecture II — Invited Papers
IMS
Organizer(s): Bodhisattva Sen, Columbia University
Chair(s): Liza Levina, University of Michigan
4:05 PM Modeling and Estimating Large Sparse Networks: Wald Lectures I and II
Jennifer Chayes, University of California, Berkeley
5:45 PM Floor Discussion
 
 

434 		Thu, 8/12/2021, 4:00 PM - 5:50 PM Virtual
Recent Advances in Unlinked and Permuted Regression — Topic-Contributed Papers
IMS, Government Statistics Section, Section on Statistical Learning and Data Science
Organizer(s): Charles Raouf Doss, University of Minnesota
Chair(s): Guangwei Weng, University of Minnesota
4:05 PM Multivariate Regression with Unknown Permutation
Martin Slawski, George Mason University; Bodhisattva Sen, Columbia University
4:25 PM Isotonic Regression with Unknown Permutations: Statistics, Computation, and Adaptation
Ashwin Pananjady, Georgia Tech; Richard J. Samworth, University of Cambridge
4:45 PM Optimal Permutation Recovery in Permuted Monotone Matrix Model
Rong Ma, University of Pennsylvania; Tony Cai, University of Pennsylvania; Hongzhe Li, University of Pennsylvania
5:05 PM Discussant: Charles Raouf Doss, University of Minnesota
5:25 PM Floor Discussion
 
 

437 		Thu, 8/12/2021, 4:00 PM - 5:50 PM Virtual
Misspecification, Robustness, and Model Assessment — Topic-Contributed Papers
Section on Bayesian Statistical Science, International Society for Bayesian Analysis (ISBA), IMS
Organizer(s): Jeffrey W Miller, Harvard University
Chair(s): Tamara Broderick, MIT
4:05 PM An Automatic Finite-Sample Robustness Metric: Can Dropping a Little Data Change Conclusions? Presentation
Ryan Giordano, Massachusetts Institute of Technology; Rachael Meager, London School of Economics; Tamara Broderick, MIT
4:25 PM Synthetic Likelihood in Misspecified Models: Consequences and Robustness
David Tyler Frazier, Monash University
4:45 PM Statistical Inference with Stochastic Gradient Algorithms
Jonathan H Huggins, Boston University
5:05 PM Approximating Cross-Validation: Guarantees for Model Assessment and Selection
Ashia Wilson, MIT
5:25 PM Robust and Reproducible Model Selection Using Bagged Posteriors
Jeffrey W Miller, Harvard University; Jonathan H Huggins, Boston University
5:45 PM Floor Discussion
 
 

444 		Thu, 8/12/2021, 4:00 PM - 5:50 PM Virtual
Recent Advances in Statistical Methodology for Big Data — Contributed Speed
IMS
Chair(s): Zhimei Ren, Stanford University
4:05 PM Bayesian Generalized Linear Model for Difference of Over or Under Dispersed Counts
Andrew W Swift, University of Nebraska at Omaha; Kimberly Sellers, Georgetown University / U.S. Census Bureau
4:10 PM An Efficient Monte Carlo EM Algorithm for Estimating Heterogenous Crossed Effects in GLMM
Rashmi Ranjan Bhuyan, University of Southern California; Gourab Mukherjee, University of Southern California; Wreetabrata Kar, Purdue University
4:15 PM Learning Trends of COVID-19 Using Semi-Supervised Clustering
Semhar Michael, South Dakota State University
4:20 PM Weak Convergence of Reversed Martingales to Mixtures of Brownian Motions
Mohamed Amezziane, Central Michigan University; Ibrahim Ahmad, Oklahoma State University
4:25 PM Population Interference in Panel Experiments
Kevin Wu Han, Department of Statistics, Stanford University; Iavor Bojinov, Harvard Business School; Guillaume Basse, Department of MS&E and Department of Statistics, Stanford University
4:30 PM Joint and Individual Variations of Sleep, Physical Activity, and Circadian Rhythmicity Features in CoLaus Study
Sun J Kang, National Institutes of Health; Andrew Leroux, University of Colorado Anschutz Medical Campus; Wei Guo, National Institutes of Health; Martin Preisig, University Hospital of Lausanne; Kathleen Merikangas, National Institute of Mental Health; Vadim Zipunnikov, Johns Hopkins Bloomberg School of Public Health
4:35 PM Some Results on Identifiable Parameters That Cannot Be Identified from Data, Including Constant Correlation Between Gaussian Observations
Christian Hennig, University of Bologna
4:40 PM On Measuring Model Complexity in Heteroskedastic Linear Regression
Bo Luan, The Ohio State University; Yoonkyung Lee, Ohio State University; Yunzhang Zhu, Ohio State University
4:45 PM Density Deconvolution with Nonstandard Error Distributions: Rates of Convergence and Adaptive Estimation
Alexander Goldenshluger, University of Haifa; Taeho Kim, University of Haifa
4:55 PM The Importance of Being Correlated: Implications of Dependence in Joint Spectral Inference Across Multiple Networks Presentation
Konstantinos Pantazis, Department of Mathematics; Avanti Athreya, Department of Applied Mathematics and Statistics; Vince Lyzinski, University of Maryland; Jesus Arroyo Relión, Texas A&M University, Department of Statitics; William N. Frost, Cell Biology and Anatomy, and Center for Brain Function and Repair; Evan S. Hill, Cell Biology and Anatomy, and Center for Brain Function and Repair
5:00 PM Simultaneous Inference for the Common and Idiosyncratic of the Dynamic Factor Model
Yuanyuan Zhang, Soochow University; Jiangyan Wang, Nanjing Audit University; Xinbing Kong, Nanjing Audit University
5:05 PM ZAP: Z-Value-Based Covariate-Adaptive Multiple Testing Presentation
Wenguang Sun, University of Southern California; Dennis Leung, University of Melbourne
5:10 PM A Central Limit Theorem for the Benjamini-Hochberg False Discovery Proportion Under a Factor Model
Dan M. Kluger, Stanford University; Art Owen, Stanford University
5:15 PM Free-Knot Spline and Its Confidence Bands for Generalized Regression Models
Elena Elisa Graetz, University of Illinois at Chicago; Jing Elisa Wang, University of Illinois at Chicago
5:20 PM Fast and Scalable SPCA via Statistical Modeling Reductions
Kayhan Behdin, MIT; Rahul Mazumder, Massachusetts Institute of Technology
5:25 PM The Parametric Weight Functions for the Analysis of Size-Biased Data Using the Weighted Lognormal Distribution and Related Estimation Procedures
Makarand V Ratnaparkhi, Wright State University
5:30 PM Convergence Rates of Two-Component MCMC Samplers
Qian Qin, University of Minnesota; Galin Jones, University of Minnesota
5:35 PM Quantifying Rounding-Induced Error for Non-Negative Discrete Random Variables
Roberto Rivera, University of Puerto Rico at Mayaguez; Axel Cortes Cubero, University of Puerto Rico at Mayaguez; Roberto Reyes, University of Puerto Rico at Mayaguez; Wolfgang Rolke, University of Puerto Rico at Mayaguez
5:40 PM Floor Discussion
 
 
 
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