Schedule for WHOA-PSI-2018

$wustl.jpg$ Contact: Todd Kuffner, email: kuffner@wustl.edu

Schedule (a detailed schedule in .pdf form is available by clicking here)

Saturday, September 8th

Breakfast and Registration	6:30 - 8:15
Introductions	8:20	Organizing Commmittee
Session 1	Chair: Dalia Ghanem UC Davis
	8:30	Joshua Loftus New York University	Model selection bias invalidates goodness of fit tests
	9:00	Tracy Ke Harvard University	Covariate assisted variable ranking
	9:30	Lucas Janson Harvard University	Should we model X in high-dimensional inference?
Coffee Break	10:00 - 10:30
Session 2	Chair: John Kolassa Rutgers University
	10:30	Aaditya Ramdas Carnegie Mellon University	Towards ``simultaneous selective inference" a new framework for multiple testing
	11:00	Hongyuan Cao Florida State University	Statistical methods for integrative analysis of multi-omics data
	11:30	Taps Maiti Michigan State University	High dimensional discriminant analysis for spatially dependent data
Lunch	12:00 - 1:30
Session 3	Chair: Nick Syring Washington University in St. Louis
	1:30	Alessandro Rinaldo Carnegie Mellon University	Optimal rates for density-based clustering using DBSCAN
	2:00	Helen Zhang University of Arizona	Oracle p-value and variable screening
	2:30	Jessie Jeng NC State University	Efficient signal inclusion in large-scale data analysis
Coffee Break	3:00 - 3:30
Session 4	Chair: Andrew Womack Indiana University
	3:30	Liza Levina University of Michigan	Matrix completion in network analysis
	4:00	Xiao-Li Meng Harvard University	Was there ever a pre-selection inference?
Coffee Break	4:30 - 5:00
Session 5	Chair: Heather Battey Imperial College London
	5:00	Andreas Buja University of Pennsylvania	PoSI under Misspecification in high-dimensions and Construction of PoSI Statistics
	5:30	Linda Zhao University of Pennsylvania	Generalized CP (GCp) in a model lean framework
Poster Session and Banquet	6:15
	Poster Presenters	Gene Katsevich Stanford University	Reconciling FDR control with post hoc filtering
		Stephen Bates Stanford University	Model-X knockoffs for graphical models
		Martin Spindler University of Hamburg	Uniform inference in high-dimensional Gaussian graphical models
		Haoyang Liu University of Chicago	Between hard and soft thresholding: optimal iterative thresholding algorithms
		Thomas Berrett University of Cambridge	Efficient integral functional estimation via k-nearest neighbour distances
		Byol Kim University of Chicago	Statistical inference for high-dimensional differential networks
		Mona Azadkia Stanford University	Matrix denoising with unknown noise variance
		Yet Nguyen Old Dominion University	Identifying relevant covariates in RNA-seq analysis by pseudo-variable augmentation
		Ran Dai University of Chicago	Post-selection inference on high-dimensional varying-coefficient quantile regression model
		John Kolassa Rutgers University	Conditional likelihood techniques applied to partial likelihood regression for survival data

Sunday, September 9th

Breakfast and Registration	6:30 - 7:55
Session 6	Chair: Arun Kumar Kuchibhotla University of Pennsylvania
	8:00	Genevera Allen Rice University	Inference, computation, and visualization for convex clustering and biclustering
	8:30	Rina Foygel Barber University of Chicago	Robust inference with the knockoff filter
	9:00	Karim Abadir Imperial College London / American University in Cairo	Link of moments before and after transformations, with an application to resampling from fat-tailed distributions
Coffee Break	9:30 - 10:00
Session 7	Chair: Liberty Vittert Washington University in St. Louis
	10:00	Lan Wang University of Minnesota	A tuning-free approach to high-dimensional regression
	10:30	Soumendra Lahiri NC State University	On limit horizons in high dimensional inference
	11:00	Kai Zhang UNC Chapel Hill	BET on independence
Lunch and Poster Session	11:30 - 1:00
	Poster Presenters	Qiyiwen Zhang Washington University in St. Louis	Bayesian variable selection and frequentist post-selection inference
		Chathurangi Pathiravasan SIU Carbondale	Bootstrapping hypotheses tests
		Keith Levin University of Michigan	Inferring low-rank population structure from multiple network samples
		Miles Lopes UC Davis	Bootstrapping spectral statistics in high dimensions
		Zhipeng Wang Genentech	TBD
		Lei Sun University of Chicago	Empirical Bayes normal means with correlated noise
		Cornelis Potgieter Southern Methodist University	Simulation-selection-extrapolation: estimation for high dimensional errors-in-variables models
		Chiao-Yu Yang UC Berkeley	TBD
		Andrew Womack Indiana University	Horseshoes with heavy tails
		Lihua Lei UC Berkeley	TBD
Session 8	Chair: Xinwei Zhang Rutgers University
	1:00	Cun-Hui Zhang Rutgers University	Higher criticism, SPRT and test of power one
	1:30	Ryan Tibshirani Carnegie Mellon University	The LOCO parameter: the good, the bad, and the ugly (or: How I learned to stop worrying and love prediction)
	2:00	Eric Laber NC State University	Sample size calculations for SMARTs
Coffee Break	2:30 - 3:00
Session 9	Chair: Joshua Loftus New York University
	3:00	Heather Battey Imperial College London	Large numbers of explanatory variables
	3:30	Rob Tibshirani Stanford University	Some new ideas for post selection inference and model assessment
Coffee Break	4:00 - 4:30
Session 10	Chair: Xiao-Li Meng Harvard University
	4:30	Richard Samworth University of Cambridge	Classification with imperfect training labels
	5:00	Emmanuel Candes Stanford University	What do we really know about logistic regression? A modern maximum-likelihood theory

Monday, September 10th

Breakfast	6:30 - 7:55
Session 11	Chair: Daniel McDonald Indiana University
	8:00	Will Fithian UC Berkeley	AdaPT: An interactive procedure for multiple testing with side information
	8:30	Jelena Bradic UC San Diego	Semi-supervised high-dimensional learning: in search of optimal inference
	9:00	Pierre Bellec Rutgers University	Model selection, model averaging?
Coffee Break	9:30 - 10:00
Session 12	Chair: Jelena Markovic Stanford University
	10:00	Jonathan Taylor Stanford University	Approximate selective inference via maximum likelihood
	10:30	Ana-Maria Staicu NC State University	Variable selection in functional linear model with varying smooth effects
	11:00	Nancy Reid University of Toronto	A new look at F-tests
Lunch	11:30 - 1:00
Session 13	Chair: Likai Chen Washington University in St. Louis
	1:00	Jan Hannig UNC Chapel Hill	Model selection without penalty using generalized fiducial inference
	1:30	Yunjin Choi National University of Singapore	Community detection via fused penalty
	2:00	Po-Ling Loh University of Wisconsin	Scale calibration for high-dimensional robust regression