Name: 2020 Joint Statistical Meetings
Start: 2020-08-02T07:00:00+00:00
End: 2020-08-06

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* = applied session ! = JSM meeting theme

Activity Details

7 !	Mon, 8/3/2020, 10:00 AM - 11:50 AM	Virtual
The Statistica Sinica Invited Session — Invited Papers
International Chinese Statistical Association, ASA Development Committee, IMS
Organizer(s): Yazhen Wang Wang, University of Wisconsin-Madison
Chair(s): Yazhen Wang Wang, University of Wisconsin-Madison
10:05 AM	Confidence Intervals for High-Dimensional Cox Models Richard Samworth, University of Cambridge
10:45 AM	Optimal Gaussian Approximation for Multiple Time Series Wei Biao Wu, University of Chicago; Sayar Karmakar, University of Florida
11:25 AM	Floor Discussion

13 *	Mon, 8/3/2020, 10:00 AM - 11:50 AM	Virtual
Recent Progress on Knockoffs Theory and Applications — Invited Papers
IMS
Organizer(s): Emmanuel Candes, Stanford University
Chair(s): Emmanuel Candes, Stanford University
10:05 AM	Controlling for Confounders Through Approximate Sufficiency Rina Foygel Barber, University of Chicago; Lucas Janson, Harvard University
10:35 AM	Model-X Power Analysis Presentation Lucas Janson, Harvard University; Wenshuo Wang, Harvard University
11:05 AM	Theory for Conditional Independence Testing Under Model-X Presentation Eugene Katsevich, Carnegie Mellon University; Aaditya Ramdas, Carnegie Mellon University
11:35 AM	Floor Discussion

41	Mon, 8/3/2020, 10:00 AM - 2:00 PM	Virtual
Topics on Bayesian Inference — Contributed Papers
IMS
Chair(s): Adityanand Guntuboyina, University of California, Berkeley
	On the Validity of the Formal Edgeworth Expansion for Posterior Densities Presentation John Kolassa, Rutgers University; Todd Kuffner, Washington University in Saint Louis
	Crowdsourcing: Beyond Dawid-Skene Model Presentation Tony Cai, University of Pennsylvania; Ran Chen, Department of Statistics, Wharton, Upenn
	Limitations of Single-Step Drift and Minorization in Markov Chain Convergence Analysis Presentation Qian Qin, University of Minnesota; James P. Hobert, University of Florida
	Introducing an Alternative Flexible Bivariate Distribution for Count Data Expressing Data Dispersion Kimberly Weems, North Carolina Central Univ; Kimberly Sellers, Georgetown University; Tong Li, Georgetown University
	Autoregressive Models for Tensor-Valued Time Series Zebang Li, Rutgers The State Univ of NJ

98 * !	Mon, 8/3/2020, 1:00 PM - 2:50 PM	Virtual
Special Invited Session in the Honor of Professor C.R. Rao's Birth Centenary — Invited Papers
General Methodology, IMS, Biometrics Section, International Statistical Institute
Organizer(s): Arni S.R. Srinivasa Rao, Augusta University, Georgia, USA
Chair(s): Arni S.R. Srinivasa Rao, Augusta University, Georgia, USA
1:05 PM	In Honor of a Great Statistical Scientist David Cox, University of Oxford
1:35 PM	To Celebrate the Centennial of a Remarkable Contributor to the Use of Statistics to Advance Science Donald Rubin, Harvard University
2:05 PM	One Hundred Years of Geometry Bradley Efron, Stanford University
2:35 PM	Floor Discussion

102 * !	Mon, 8/3/2020, 1:00 PM - 2:50 PM	Virtual
Medallion Lecture I — Invited Papers
IMS
Organizer(s): Harrison Zhou, Yale University
Chair(s): Dylan Small, University of Pennsylvania
1:05 PM	Replication and Evidence Factors in Observational Studies Presentation Paul R Rosenbaum, Wharton School/University of Pennsylvania
2:40 PM	Floor Discussion

103 * !	Mon, 8/3/2020, 1:00 PM - 2:50 PM	Virtual
Semiparametric Inference with High-Dimensional and Complex Data — Invited Papers
ENAR, IMS, Section on Nonparametric Statistics
Organizer(s): Zhiqiang Tan, Rutgers University
Chair(s): TBD TBD, TBD
1:05 PM	A Unifying Approach for Doubly-Robust L1-Regularized Estimation of Causal Contrasts Ezequiel Smucler, Universidad Torcuato Di Tella; James Robins, Harvard T.H Chan School of Public Health; Andrea Rotnitzky, Universidad Torcuato Di Tella
1:30 PM	Convex Loss Versus Semiparametric Likelihood Machine Learning Estimates Michael R. Kosorok, University of North Carolina at Chapel Hill
1:55 PM	Limit Distribution Theory for Multiple Isotonic Regression Qiyang Han, Rutgers University; Cun-Hui Zhang, Rutgers University
2:20 PM	Discussant: Zhiqiang Tan, Rutgers University
2:45 PM	Floor Discussion

105 * !	Mon, 8/3/2020, 1:00 PM - 2:50 PM	Virtual
Deep Learning and Statistical Modeling with Applications — Invited Papers
International Chinese Statistical Association, Section on Statistical Learning and Data Science, IMS
Organizer(s): Ji Zhu, University of Michigan
Chair(s): Ji Zhu, University of Michigan
1:05 PM	Deep Learning and Statistical Modeling with Applications Yingying Fan, USC
1:30 PM	Beyond Shallow Learning: New Results for Matrix Completion Jianqing Fan, Princeton University; Yuxin Chen, Princeton University; Cong Ma, Princeton University; Yulin Yan, Princeton University
1:55 PM	Statistical Challenges in Analyzing Two-Sided Marketplace HONGTU ZHU, DiDi
2:20 PM	From Classical Statistics to Modern Machine Learning Mikhail Belkin, Ohio State University
2:45 PM	Floor Discussion

126 * !	Mon, 8/3/2020, 1:00 PM - 2:50 PM	Virtual
Recent Advances in Bayesian Mixed Membership Modeling for Network, Longitudinal, and Multivariate Data — Topic Contributed Papers
Section on Bayesian Statistical Science, International Society for Bayesian Analysis (ISBA), IMS, Text Analysis Interest Group
Organizer(s): Elena A Erosheva, University of Washington ; Gongjun Xu, University of Michigan
Chair(s): Tanzy Love, University of Rochester
1:05 PM	Exponential Family Mixed Membership Models for Soft Clustering of Multivariate Data Brendan Murphy, University College Dublin; Arthur White, Trinity College Dublin
1:25 PM	A New Class of Mixed Membership Models for Educational Testing: Partial-Mastery Cognitive Diagnosis Models Elena A Erosheva, University of Washington ; Zhuoran Shang , University of Michingan; Gongjun Xu, University of Michigan
1:45 PM	Multilevel Mixed Membership Stochastic Block Models Tracy Sweet
2:05 PM	Longitudinal Structural Mixed Membership Models for Estimating Latent Health Trajectories Using Administrative Claims Data Zhenke Wu, University of Michigan; Mengbing Li, University of Michigan
2:25 PM	Detectability Limits in Dynamic Networks with Link Persistency Amir Ghasemian
2:45 PM	Floor Discussion

138	Tue, 8/4/2020, 10:00 AM - 11:50 AM	Virtual
Digging into Models: Statistical Theory Inspired by Environmental Applications — Invited Papers
Section on Statistics and the Environment, International Indian Statistical Association, IMS
Organizer(s): William Kleiber, University of Colorado
Chair(s): Douglas Nychka, Colorado School of Mines
10:05 AM	Change-Set Analysis and Related Asymptotics with Application to Spatial Clustering in Environmental Health Jun Zhu, University of Wisconsin; Pei-Sheng Lin, National Health Research Institutes
10:30 AM	Inverse and Decorrelating Operators for Matern Covariances Joseph Guinness, Cornell University
10:55 AM	Whittle Likelihood for Irregularly Spaced Spatial Data Soutir Bandyopadhyay, Colorado School of Mines
11:20 AM	The Matérn Covariance Function on the Sphere Emilio Porcu, Trinity College at Dublin
11:45 AM	Floor Discussion

141 !	Tue, 8/4/2020, 10:00 AM - 11:50 AM	Virtual
Minimax Theory for High-Dimensional Models — Invited Papers
IMS
Organizer(s): Alexandre Tsybakov, CREST, ENSAE
Chair(s): Mohamed Ndaoud, USC
10:05 AM	Estimation of Wasserstein Distances in the Spiked Transport Model Jonathan Niles-Weed, New York University; Philippe Rigollet, Massachusetts Institute of Technology
10:35 AM	Dualizing Le Cam's Method, with Applications to Estimating the Unseens Yihong Wu, Yale University; Yury Polyanskiy, MIT
11:05 AM	All-In-One Robust Estimator of the Gaussian Mean Arnak S. Dalalyan, CREST - ENSAE - IP Paris
11:35 AM	Floor Discussion

174	Tue, 8/4/2020, 10:00 AM - 2:00 PM	Virtual
Statistical Optimality in High-Dimensional Models and Tradeoffs with Computational Complexity, Privacy and Communication Constraints — Contributed Papers
IMS
Chair(s): Adityanand Guntuboyina, University of California, Berkeley
	The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy Yichen Wang, The Wharton School, University of Pennsylvania; Tony Cai, University of Pennsylvania; Linjun Zhang, Rutgers University
	A Precise High-Dimensional Asymptotic Theory for Boosting Pragya Sur, Harvard University; Tengyuan Liang, University of Chicago
	Optimal and Adaptive Estimation of Extreme Values in the Permuted Monotone Matrix Model Rong Ma, University of Pennsylvania; Tony Cai, University of Pennsylvania; Hongzhe Li, University of Pennsylvania
	The Overlap Gap Property in Planted Submatrix Recovery Subhabrata Sen, Harvard University; David Gamarnik, Massachusetts Institute of Technology; Aukosh Jagannath, University of Waterloo
	Distributed Gaussian Mean Estimation Under Communication Constraints: Optimal Rates and Communication-Efficient Algorithms Hongji Wei, Wharton Department of Statistics; Tony Cai, University of Pennsylvania
	Fundamental Barriers to Tractable Estimation in High-Dimensions Presentation Michael Celentano, Stanford University; Andrea Montanari, Stanford University; Yuchen Wu, Stanford University

241 *	Tue, 8/4/2020, 1:00 PM - 2:50 PM	Virtual
Medallion Lecture II — Invited Papers
IMS
Organizer(s): Harrison Zhou, Yale University
Chair(s): Nancy Reid, University of Toronto
1:05 PM	Where Is the Randomness: Features or Samples? Susan Holmes, Stanford University
2:45 PM	Floor Discussion

260 * !	Tue, 8/4/2020, 1:00 PM - 2:50 PM	Virtual
Statistics and AI in Music — Topic Contributed Papers
Royal Statistical Society, Section on Statistical Learning and Data Science, IMS
Organizer(s): Jan Beran, University of Konstanz
Chair(s): Philipp Sibbertsen, Leibniz Universitaet Hannover
1:05 PM	Understanding Audio from Music Practice Sessions Christopher Raphael, Indiana University
1:25 PM	Visualizing Music Information: Classical Composers Networks and Similarities Presentation Patrick Georges, University of Ottawa
1:45 PM	Statistics and AI in Music Ahmed Elgammal, Artrendex / Rutgers University; Mark Gotham, Universität des Saarlandes / Cornell
2:05 PM	Fusing Audio and Semantic Technologies: Applying AI, Machine Learning and Data Science to Music Production and Consumption Mark Sandler, Queen Mary University of London; Johan Pauwels, Queen Mary University of London; David De Roure, University of Oxford; Kevin Page, University of Oxford
2:25 PM	Discussant: Jan Beran, University of Konstanz
2:45 PM	Floor Discussion

261	Tue, 8/4/2020, 1:00 PM - 2:50 PM	Virtual
High-Dimensional Statistical Inference Meets Large-Scale Optimization — Topic Contributed Papers
IMS, JASA, Theory and Methods
Organizer(s): Yuxin Chen, Princeton University
Chair(s): Yuxin Chen, Princeton University
1:05 PM	Hierarchical Clustering via Spectral Methods in Networks Xiaodong Li, UC Davis
1:25 PM	Understanding the Effect of Learning Rate in Deep Learning Weijie Su, University of Pennsylvania
1:45 PM	The Distribution of Lasso and Its Applications: Arbitrary Covariance Yuting Wei, Carnegie Mellon University
2:05 PM	Statistical Learning with Stochastic Gradient Flow Edgar Dobriban, University of Pennsylvania
2:25 PM	On Interpolating Estimators and Adversarial Examples Fanny Yang, ETH Zürich
2:45 PM	Floor Discussion

264 * !	Tue, 8/4/2020, 1:00 PM - 2:50 PM	Virtual
New Statistical Methods for Longitudinal Data Analysis — Topic Contributed Papers
Section on Nonparametric Statistics, International Chinese Statistical Association, IMS
Organizer(s): Anne Buu, UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
Chair(s): Runze Li, Pennsylvania State University
1:05 PM	Modeling of Business Reopening when Facing SARS-CoV-2 Pandemic: Protection, Cost and Risk Hongyu Miao, UT Health At Houston; Chengxue Zhong, UTHealth
1:25 PM	Analysis of Longitudinal Categorical Data Using a Continuous Time Semi-Markov Chain Model Kusha Mohammadi, Univeristy of Texas- Health Science Center at Houston; Wenyaw Chan, University of Texas-Health Science Center at Houston; Valory N Pavlik, Baylor College of Medicine
1:45 PM	Multivariate Partial Linear Varying-Coefficient Model for G×E Studies with Longitudinal Traits Yuehua Cui, Michigan State University
2:05 PM	Floor Discussion

282 * !	Wed, 8/5/2020, 10:00 AM - 11:50 AM	Virtual
Complex Functional Data Analysis with Biomedical Applications — Invited Papers
Section on Nonparametric Statistics, Biometrics Section, IMS
Organizer(s): Kuang-Yao Lee, Temple University
Chair(s): Ana Kenney, Pennsylvania State University
10:05 AM	Domain Selection for Functional Linear Models: A Dynamic RKHS Approach Jane-Ling Wang, UC Davis
10:30 AM	On Sufficient Graphical Models Bing Li, Pennsylvania State University; Kyongwon Kim, Pennsylvania State University
10:55 AM	Nonparametric Functional Graphical Models Kuang-Yao Lee, Temple University; Lexin Li, University of California, Berkeley; Bing Li, Pennsylvania State University; Hongyu Zhao, Yale University
11:20 AM	Correcting Batch Effects in the Covariance Structures of Spatially-Dependent Multivariate Object Andrew Chen, University of Pennsylvania; Russell Shinohara, University of Pennsylvania; Haochang Shou, University of Pennsylvania
11:45 AM	Floor Discussion

283	Wed, 8/5/2020, 10:00 AM - 11:50 AM	Virtual
Theoretical Advances in Deep Learning — Invited Papers
IMS, Section on Nonparametric Statistics, International Indian Statistical Association
Organizer(s): Po-Ling Loh, UW-Madison
Chair(s): Po-Ling Loh, UW-Madison
10:05 AM	Good Linear Classifiers Are Abundant in the Interpolating Regime Jason Klusowski, Rutgers University; Ryan Theisen, UC Berkeley; Michael Mahoney, UC Berkeley
10:20 AM	Multiple Descent Phenomenon, Risk of Minimum-Norm Interpolants and Restricted Lower Isometry of Kernels Tengyuan Liang, University of Chicago
10:35 AM	Polylogarithmic Width Suffices for Gradient Descent to Achieve Arbitrarily Small Test Error with Shallow ReLU Networks Matus Telgarsky, University of Illinois - Urbana Champaign
10:50 AM	Discussant: Edgar Dobriban, University of Pennsylvania
11:05 AM	Discussant: Daniel Hsu, Columbia University
11:20 AM	Discussant: Mikhail Belkin, Ohio State University
11:30 AM	Floor Discussion

286	Wed, 8/5/2020, 10:00 AM - 11:50 AM	Virtual
Learning Networks from Point Processes: Neuronal Connectivity Networks and Beyond — Invited Papers
Section on Statistical Learning and Data Science, IMS, ENAR
Organizer(s): Ali Shojaie, University of Washington
Chair(s): Ali Shojaie, University of Washington
10:05 AM	Context-Dependent Self-Exciting Point Processes: Models, Methods, and Risk Bounds in High Dimensions Garvesh Raskutti, UW-Madison; Lili Zheng, University of Wisconsin-Madison; Rebecca Willett, University of Chicago
10:30 AM	A Universal Nonparametric Event Detection Framework for Neuropixels Data Shizhe Chen, University of California, Davis; Hao Chen, University of California, Davis; Xinyi Deng, Columbia University
10:55 AM	Latent Network Structure Learning from High-Dimensional Multivariate Point Processes Biao Cai, University of Miami; Emma Jingfei Zhang, University of Miami; Yongtao Guan, University of Miami
11:20 AM	Theory and Modeling for the Truncated Hawkes Process Victor Solo, UNSW, Sydney
11:45 AM	Floor Discussion

287 *	Wed, 8/5/2020, 10:00 AM - 11:50 AM	Virtual
Current and Future Challenges in Analyzing Composite Endpoints — Invited Papers
Lifetime Data Science Section, Biometrics Section, IMS
Organizer(s): Li-Shan Huang, National Tsing Hua University, TAIWAN
Chair(s): Li-Shan Huang, National Tsing Hua University, TAIWAN
10:05 AM	On the Intransitivity of the Win Ratio David Oakes, University of Rochester
10:30 AM	Benefit-Risk Assessment Using a Primary Endpoint and Secondary Measurements Mei-Cheng Wang, Johns Hopkins University
10:55 AM	Analysis of Cardiovascular Clinical Trials with Random Effects on Health Conditions at Entry Mei-Ling Ting Lee, University of Maryland; John Lawrence, US FDA; Yiming Chen, University of Maryland, College Park; H. M. James Hung, CDER at FDA
11:20 AM	Joint Bayesian Nonparametric Models for Survival Times and Medical Costs Jason Roy, Rutgers University; Arman Oganisian, University of Pennsylvania; Nandita Mitra, University of Pennsylvania
11:45 AM	Floor Discussion

292	Wed, 8/5/2020, 10:00 AM - 11:50 AM	Virtual
Nonparametric and High-Dimensional Bayes: Uncertainty Quantification, Computation, and Posterior Contraction — Invited Papers
IMS, International Society for Bayesian Analysis (ISBA)
Organizer(s): Aad van der Vaart, Leiden University
Chair(s): Aad van der Vaart, Leiden University
10:05 AM	Convergence Rates of Variational Bayes and Empirical Bayes: A Unified Analysis Chao Gao, University of Chicago
10:30 AM	Bayesian Trees Are Spatially Adaptive Veronika Rockova, University of Chicago; Judith Rousseau, Oxford University
10:55 AM	Posterior Convergence Rate and Sharp Minimaxity for Sparse Sequences Ismaël Castillo, Sorbonne University
11:20 AM	Discussant: Edward George, University of Pennsylvania
11:40 AM	Floor Discussion

305 *	Wed, 8/5/2020, 10:00 AM - 11:50 AM	Virtual
Asymmetry in Objectives and Samples for Classification and Multiple Testing — Topic Contributed Papers
WNAR, IMS, Biometrics Section
Organizer(s): Xin Tong, University of Southern California
Chair(s): Jingyi Jessica Li, University of California, Los Angeles
10:05 AM	Optimal Hypergeometric Confidence Intervals Lijia Wang, University of Southern California; Jay Bartroff, University of Southern California; Gary Lorden, California Institute of Technology
10:25 AM	Neyman-Pearson Classification Under Label Noise Shunan Yao, University of Southern California; Bradley Rava, University of Southern California; Xin Tong, University of Southern California; Gareth James, University of Southern California
10:45 AM	Neyman-Pearson Classification of Dependent Data Yusheng Wu; Shunan Yao, University of Southern California; Xin Tong, University of Southern California
11:05 AM	Floor Discussion

306	Wed, 8/5/2020, 10:00 AM - 11:50 AM	Virtual
Algorithmic and Inferential Advances in Univariate and Multivariate Tuning-Parameter-Free Nonparametric Procedures — Topic Contributed Papers
Section on Statistical Learning and Data Science, Section on Nonparametric Statistics, IMS
Organizer(s): Charles Doss, University of Minnesota
Chair(s): Guangwei Weng, University of Minnesota
10:05 AM	Multivariate Rank-Based Distribution-Free Nonparametric Testing Using Measure Transportation Bodhisattva Sen, Columbia University; Nabarun Deb, Columbia University
10:25 AM	Likelihood Ratio Tests and Confidence Intervals Based on the Shape Constraint of Concavity Charles Doss, University of Minnesota; Jon Wellner, University of Washington
10:45 AM	Multivariate Adaptation in Log-Concave Density Estimation Arlene K. H. Kim, Korea University; Richard Samworth, University of Cambridge; Oliver Feng, University of Cambridge; Adityanand Guntuboyina, University of California, Berkeley
11:05 AM	Dyadic CART Revisited Sabyasachi Chatterjee, University of Illinois at Urbana-Champai
11:25 AM	Learning Multivariate Log-Concave Densities Ilias Diakonikolas, UW Madison
11:45 AM	Floor Discussion

324	Wed, 8/5/2020, 10:00 AM - 2:00 PM	Virtual
Causal Inference, Empirical Bayes and Related Topics in Regression — Contributed Papers
IMS
	Compound Empirical Bayes Interval Estimation Wenhua Jiang, Fudan University; Cun-Hui Zhang, Rutgers University
	Sample Size Estimation and Power Analysis in Longitudinal and Crossover Cluster Randomized Trials Jijia Wang, UT Southwestern Medical Center
	Irrational Exuberance: Correcting Bias in Probability Estimates Presentation Bradley Rava, University of Southern California; Gareth James, University of Southern California; Peter Radchenko, University of Sydney
	Model Complexity and Prediction Error in Modern Predictive Settings Presentation Bo Luan, Ohio State University; Yoonkyung Lee, Ohio State University; Yunzhang Zhu, Ohio State University
	Conformal Inference for Heterogeneous Treatment Effect Lihua Lei, Stanford University; Emmanuel Candes, Stanford University

363	Wed, 8/5/2020, 10:00 AM - 2:00 PM	Virtual
Contributed Poster Presentations: IMS — Contributed Poster Presentations
IMS
1:	Analysis of Multilevel Data with Missing Information About Correlation Structures Tiantian Yang, Clemson University; William Bridges, Clemson University ; Deborah Kunkel, Clemson University
2:	Polluted Bootstrap Percolation in Two Dimensions with a General Neighborhood Structure Amartya Ghosh, The Ohio State University; Samuel Mossing, The Ohio State University; David Sivakoff, The Ohio State University
3:	Exact Simulation of Diffusions Revisited Kumar Somnath, The Ohio State University; Radu Herbei, The Ohio State University
4:	Block Gibbs Samplers for Logistic Mixed Models: Convergence Properties and Comparison with Full Gibbs Samplers Yalin Rao, Iowa State Univ; Vivekananda Roy, Iowa State University
5:	Selecting meaningful principal components in heterogeneous data using signflips David Hong, University of Pennsylvania; Yue Sheng, University of Pennsylvania; Edgar Dobriban, University of Pennsylvania

390 * !	Wed, 8/5/2020, 1:00 PM - 2:50 PM	Virtual
The Best of the Annals of Applied Statistics (AOAS) — Invited Papers
IMS
Organizer(s): Josee Dupuis, Boston University School of Public Health
Chair(s): Josee Dupuis, Boston University School of Public Health
1:05 PM	Dynamics of Homelessness in Urban America Chris Glynn, University of New Hampshire; Emily B. Fox, University of Washington
1:35 PM	SHOPPER: A Probabilistic Model of Consumer Choice with Substitutes and Complements Presentation Francisco Ruiz, Deepmind; Susan Athey, Stanford University; David Blei, Columbia University
	Discussant: Beth Ann Griffin, RAND
2:05 PM	Discussant: Karen Kafadar, University of Virginia
2:35 PM	Floor Discussion

413 *	Wed, 8/5/2020, 1:00 PM - 2:50 PM	Virtual
Time Series with a Twist — Topic Contributed Papers
Business and Economic Statistics Section, Section on Nonparametric Statistics, IMS
Organizer(s): David S. Matteson, Cornell University
Chair(s): David S. Matteson, Cornell University
1:05 PM	Simultaneous Transformation and Rounding (STAR) Models for a Time Series of Counts Daniel Kowal, Rice University; Brian King, Rice University
1:25 PM	REMIS: Retrieval from Mixed Sampling Frequency Data: G-Identifiability and Estimation of Regular and Singular VAR(MA) Systems Manfred Deistler, Vienna University of Technology; Philipp Gersing, Vienna University of Technology, Institute for Advanced Studies Vienna
1:45 PM	Assessing Macroeconomic Tail Risks in a Data-Rich Environment Presentation Taeyoung Doh, Federal Reserve Bank of Kansas City; Thomas Cook, Federal Reserve Bank of Kansas City
2:05 PM	Random Forests for Time Series Forecasting Barbara Bailey, San Diego State University
2:25 PM	Floor Discussion

422 * !	Thu, 8/6/2020, 10:00 AM - 11:50 AM	Virtual
Medallion Lecture III — Invited Papers
IMS
Organizer(s): Harrison Zhou, Yale University
Chair(s): Xuming He, University of Michigan
10:05 AM	Unlikely Likelihoods Presentation Roger Koenker, University College London
11:40 AM	Floor Discussion

438	Thu, 8/6/2020, 10:00 AM - 11:50 AM	Virtual
Statistical Methods for Topological Data Analysis — Topic Contributed Papers
Section on Statistical Learning and Data Science, Korean International Statistical Society, IMS
Organizer(s): Chul Moon, Southern Methodist University
Chair(s): Hengrui Luo, The Ohio State University
10:05 AM	Solution Manifold and Its Statistical Applications Yen-Chi Chen, University of Washington
10:25 AM	Persistent Topological Descriptors for Functional Brain Network Hyunnam Ryu, University of Georgia; Nicole Lazar, University of Georgia
10:45 AM	Uncovering the Holes in the Universe with Topological Data Analysis Jessi Cisewski-Kehe, Yale University
11:05 AM	Confidence Band for Persistent Homology Presentation Jisu Kim, Inria
11:25 AM	Discussant: Chul Moon, Southern Methodist University
11:45 AM	Floor Discussion

456 !	Thu, 8/6/2020, 10:00 AM - 11:50 AM	Virtual
P-Values and "Statistical Significance": Deconstructing the Arguments — Topic Contributed Panel
Section on Statistical Consulting, Biometrics Section, IMS
Organizer(s): Deborah Mayo, Virginia Tech
Chair(s): Larry Wasserman, Carnegie Mellon University
10:05 AM	P-values and "Statistical Significance": Deconstructing the Arguments Presentation
Panelists:	Deborah Mayo, Virginia Tech Karen Kafadar, University of Virginia Ya’acov Ritov, University of Michigan Stanley Young, CGStat
11:40 AM	Floor Discussion

468	Thu, 8/6/2020, 10:00 AM - 2:00 PM	Virtual
Modern Topics in Hypothesis Testing — Contributed Papers
IMS
Chair(s): Adityanand Guntuboyina, University of California, Berkeley
	The Significance of Statistical Significance Hal Switkay, Goldey-Beacom College
	Testing for Heteroscedasticity in Functional Linear Models Presentation James Cameron, George Mason University; Pramita Bagchi, George Mason University
	A Generalized Family of Fisher's P-Value Combination Tests and Their Null Distributions Under Correlation Hong Zhang, Merck & Co., Inc.; Zheyang Wu, Worcester polytechnic Institute
	Analysis of an EEG Experiment by a Multiple Testing Procedure Shinjini Nandi, New York University, School of Medicine; Sanat Sarkar, Temple University
	The Robustness of Covtest in Exponential Family Dewei Zhong; John Kolassa, Rutgers University
	Adaptive Inference for Change Points in High-DimensionalData Yangfan Zhang; Runmin Wang, UIUC; Xiaofeng Shao, University of Illinois at Urbana-Champaign

469	Thu, 8/6/2020, 10:00 AM - 2:00 PM	Virtual
Topics in Modern Predictive Modeling — Contributed Papers
IMS
Chair(s): Adityanand Guntuboyina, University of California, Berkeley
	Predictive Modeling for Positive-Only Data with High-Dimensional Covariates Presentation Prabrisha Rakshit, Rutgers The State Univ of NJ; Zijian Guo, Rutgers The State University of NJ; Jinbo Chen, University of Pennsylvania; Daniel Herman, University of Pennsylvania Perelman School of Medicine
	The Price of Competition: Effect-Size Heterogeneity Matters in High Dimensions Hua Wang, University of Pennsylvania, Statistics Department of Wharton; Weijie Su, University of Pennsylvania; Yachong Yang, Univ of Pennsylvania, Wharton School of Business
	Multi-Product Dynamic Pricing in High-Dimensions with Heterogeneous Price Sensitivity Adel Javanmard, University of Southern California; Hamid Nazerzadeh; Simeng Shao, University of Southern California
	Fitting Bivariate Extreme Value Copulas with Polynomial Pickands Functions Berwin Turlach, University of Western Australia
	Bayesian Generalized Linear Model for Difference of Over or Under Dispersed Counts Andrew W Swift, University of Nebraska At Omaha; Kimberly Sellers, Georgetown University
	Adaptive Resistant Regression Rui Mao, University of Toronto

520 !	Thu, 8/6/2020, 1:00 PM - 2:50 PM	Virtual
New Quantile-Modeling Methods for Large-Scale Heterogeneous Data — Invited Papers
Section on Nonparametric Statistics, International Chinese Statistical Association, IMS
Organizer(s): Lan Wang, University of Minnesota
Chair(s): Qi Zheng, University of Louisville
1:05 PM	Quantile Regression Approach to Conditional Mode Estimation Kengo Kato, Cornell University; Hirofumi Ota, Rutgers University; Satoshi Hara, Osaka University
1:30 PM	Uniform Inference for Heterogeneous Quantile Treatment Effects in High Dimensions Alexander Giessing, Princeton University; Jingshen Wang, UC Berkeley
1:55 PM	Lean-Assumption Quantile Regression for High-Dimensional Data Lan Wang, University of Minnesota
2:20 PM	Discussant: Ying Wei, Columbia University
2:40 PM	Floor Discussion

523	Thu, 8/6/2020, 1:00 PM - 2:50 PM	Virtual
Causality in Statistical Data Science — Invited Papers
IMS
Organizer(s): Peter Bühlmann, ETH Zurich
Chair(s): Stefan Wager, Stanford University
1:05 PM	A Causal Perspective on Domain Adaptation Yuansi Chen, ETH Zürich; Peter Bühlmann, ETH Zurich
1:35 PM	Doubly Debiased Lasso: High-Dimensional Inference Under Hidden Confounding and Measurement Errors Zijian Guo, Rutgers The State University of NJ; Domagoj Cevid, ETH; Peter Bühlmann, ETH Zurich
2:05 PM	Bias-Aware Confidence Intervals for Empirical Bayes Analysis Stefan Wager, Stanford University; Nikos Ignatiadis, Stanford
2:35 PM	Floor Discussion

524 * !	Thu, 8/6/2020, 1:00 PM - 2:50 PM	Virtual
Emerging Statistical Learning Methods in Modern Data Science — Invited Papers
Section on Statistical Learning and Data Science, Section on Nonparametric Statistics, IMS
Organizer(s): Ping Ma, University of Georgia
Chair(s): Ping Ma, University of Georgia
1:05 PM	A Powerful AI Tool for CHD Screening Wenxuan Zhong, Department of Statistics, University of Georgia
1:30 PM	A Community Model for Partially Observed Networks from Surveys Tianxi Li, University of Virginia; Elizaveta Levina, University of Michigan; Ji Zhu, University of Michigan
1:55 PM	Reverse Engineering a Deep Network Presentation Douglas Nychka, Colorado School of Mines
2:20 PM	Statistical Methods for Some Problems in Physics Larry Wasserman, Carnegie Mellon University
2:45 PM	Floor Discussion

529	Thu, 8/6/2020, 1:00 PM - 2:50 PM	Virtual
Recent Advances in Clustering and Community Detection — Invited Papers
WNAR, IMS, ENAR
Organizer(s): Xin Tong, University of Southern California
Chair(s): Rachel Wang, University of Sydney
1:05 PM	Community Detection with Partial Information Xin Tong, University of Southern California
1:30 PM	Community Estimation in Multilayer Stochastic Block Models Jing Lei, Carnegie Mellon University
1:55 PM	Generalized R Square Measures for Capturing Mixtures of Linear Dependences Presentation Jingyi Jessica Li, University of California, Los Angeles
2:20 PM	A Flexible Latent Space Model for Multilayer Networks Ji Zhu, University of Michigan
2:45 PM	Floor Discussion

530	Thu, 8/6/2020, 1:00 PM - 2:50 PM	Virtual
New Insights on High-Dimensional Statistics — Invited Papers
IMS
Organizer(s): Zongming Ma, University of Pennsylvania
Chair(s): Zongming Ma, University of Pennsylvania
1:05 PM	Inference and Uncertainty Quantification for Noisy Matrix Completion Yuxin Chen, Princeton University
1:30 PM	Likelihood Landscape and Maximum Likelihood Estimation for the Discrete Orbit Recovery Model Zhou Fan, Yale University; Yi Sun, Columbia University; Tianhao Wang, Yale University; Yihong Wu, Yale University
1:55 PM	Improved Clustering Algorithms for Bipartite Stochastic Block Model Alexandre Tsybakov, CREST, ENSAE; Mohamed Ndaoud, USC
2:20 PM	Individual Data Protected Integrative Regression Analysis of High-Dimensional Heterogeneous Data Yin Xia, Fudan University
2:45 PM	Floor Discussion

538 !	Thu, 8/6/2020, 1:00 PM - 2:50 PM	Virtual
Emerging Topics in Private Data Analysis — Topic Contributed Papers
IMS, Section on Statistical Learning and Data Science, Royal Statistical Society
Organizer(s): Weijie Su, University of Pennsylvania
Chair(s): Weijie Su, University of Pennsylvania
1:05 PM	Differentially Private Mean and Covariance Estimation Presentation Gautam Kamath, University of Waterloo
1:25 PM	KNG: The K-Norm Gradient Mechanism Jordan Awan, Penn State University; Matthew Reimherr, Penn State University
1:45 PM	Locally Private Learning, Estimation, Inference and Optimality Feng Ruan, University of California at Berkeley
2:05 PM	Gaussian Differential Privacy, with Applications to Deep Learning Jinshuo Dong, University of Pennsylvania; Aaron Roth, University of Pennsylvania; Weijie Su, University of Pennsylvania
2:25 PM	Discussant: Xiao-Li Meng, Harvard University
2:45 PM	Floor Discussion

542	Thu, 8/6/2020, 1:00 PM - 2:50 PM	Virtual
Recent Extension from Univariate to Multivariate Analysis for High-Dimensional Data with Complex Environment — Topic Contributed Papers
Section on Statistical Computing, IMS, Korean International Statistical Society
Organizer(s): Jin-Hong Park
Chair(s): Qin Wang, University of Alabama
1:05 PM	New Class of Multiple Time Series Modeling: An Extension from Univariate Dimension Reduction Jin-Hong Park
1:25 PM	Sufficient Dimension Reduction for Matrix and Tensor Time Series Data Seyed Yaser Samadi, Southern Illinois University, Carbondale
1:45 PM	Testing Equality of Means for the Incomplete Paired Data with the IncomPair R Package Desale Habtzghi, DePaul University
2:05 PM	Robust Multivariate Mixture Estimation with Partial L2E Fikriye Kabakci, Recep Tayyip Erdogan University; Umashanger Thayasivam, Rowan University
2:25 PM	Floor Discussion

558 !	Thu, 8/6/2020, 3:00 PM - 4:50 PM	Virtual
Data and Algorithmic Biases: Systematic Harms and Potential Solutions — Invited Papers
IMS
Organizer(s): Elisa Celis, Yale
Chair(s): Elisa Celis, Yale
3:05 PM	Counterfactual risk assessment and algorithmic fairness Alexandra Chouldechova, Carnegie Mellon University
3:35 PM	COVID-19 Analysis: A Twitter-based Social Distancing Measure Samah Jarad, Yale
4:05 PM	AI Fairness in Industry: From Principles to Practice Jennifer Wortman Vaughan, Microsoft Research
4:35 PM	Floor Discussion

560	Thu, 8/6/2020, 3:00 PM - 4:50 PM	Virtual
New Development of Flexible Methods for Network Analysis — Invited Papers
IMS, Journal on Statistical Analysis and Data Mining, International Chinese Statistical Association
Organizer(s): Rui Song, NC State University
Chair(s): Chengchun Shi, The London School of Economics
3:05 PM	Testing for Balance in Social Networks Harrison Zhou, Yale University; Derek Feng, Yale University
3:30 PM	Statistics for Statisticians Jiashun Jin, Carnegie Mellon University
3:55 PM	Likelihood Inference for a Large Causal Network Chunlin Li, University of Minnesota; Xiaotong Shen, University of Minnesota; Wei Pan, University of Minnesota
4:20 PM	Why Aren’t Network Statistics Accompanied by Uncertainty Statements? Eric Kolaczyk, Boston University
4:45 PM	Floor Discussion

569 * !	Thu, 8/6/2020, 3:00 PM - 4:50 PM	Virtual
Frontier of Science, Agriculture and Food System: Global and Big Data Impact — Invited Panel
Committee of Representatives to AAAS, IMS, American Association for the Advancement of Science
Organizer(s): Jiayang Sun, USDA and George Mason University
Chair(s): Anand Vidyashankar, George Mason University
3:05 PM	Innovative AI, Statistics, GIS, and Data - Unique Government, Academia, and Industry Partnership (PDI): ASA/IMS/AMA/MAA/ACM/SIAM Science and Technology Policy Fellowship
Panelists:	Jiayang Sun, USDA and George Mason University Ranveer Chandra, Microsoft Corporation Sarah Beebout, USDA Agricultural Research Service Nick Short, Esri Michael Buser, USDA
4:40 PM	Floor Discussion

586	Thu, 8/6/2020, 3:00 PM - 4:50 PM	Virtual
Theoretical Investigations on Discrete Structure Recovery — Topic Contributed Papers
IMS, International Chinese Statistical Association, International Statistical Institute
Organizer(s): Anderson Ye Zhang, University of Pennsylvania
Chair(s): Zijian Guo, Rutgers The State University of NJ
3:05 PM	Iterative Algorithm for Discrete Structure Recovery Anderson Ye Zhang, University of Pennsylvania; Chao Gao, University of Chicago
3:25 PM	Fast and Adaptive Iterative Hard Thresholding in High-Dimensional Linear Regression: A Non-Convex Algorithmic Regularization Approach Presentation Mohamed Ndaoud, USC
3:45 PM	Edgeworth Approximation to Network U-Statistics Yuan Zhang, Ohio State University - Columbus, OH
4:05 PM	Optimal Estimation in High-Dimensional Gaussian Mixtures Natalie Doss, Yale University
4:25 PM	SDP Relaxation for Clustering Under Gaussian Mixture Model: Hidden Integrality, Statistical Optimality and Semirandom Robustness Yingjie Fei, Cornell University
4:45 PM	Floor Discussion

JSM 2020 Online Program

Activity Details

American Statistical Association