Workshops

Fall 2018

Robust and High-Dimensional Statistics

Oct 29, 2018 to Nov 2, 2018

Return to event »

Click on the titles of individual talks for abstract, slides and archived video.

Monday, October 29th, 2018
9:00 am–9:20 am		Coffee and Check-In
9:20 am–9:30 am		Opening Remarks
9:30 am–10:10 am		Robust List Decoding of Spherical Gaussians Daniel Kane (UC San Diego)
10:20 am–11:00 am		Mixture Models, Robustness, and Sum of Squares Proofs Jerry Li (Massachusetts Institute of Technology)
11:10 am–11:30 am		Break
11:30 am–12:10 pm		Computational-Statistical Tradeoffs in Robust High-Dimensional Estimation Ilias Diakonikolas (University of Southern California)
12:20 pm–2:00 pm		Lunch
2:00 pm–2:40 pm		Efficient Algorithms for Outlier-Robust Regression Adam Klivans (University of Texas, Austin)
2:50 pm–3:30 pm		Detecting Weak Signals via Hypothesis Testing Ravi Kannan (Microsoft Research India)
3:40 pm–4:00 pm		Break
4:00 pm–4:40 pm		On Using Graph Distances to Estimate Euclidean and Related Distances Ery Arias-Castro (UC San Diego)
4:50 pm–5:30 pm		The Importance of Better Models in Stochastic Optimization - Robustness, Fast Convergence, and Optimality John Duchi (Stanford University)
5:40 pm		Reception

Tuesday, October 30th, 2018
9:00 am–9:30 am		Coffee and Check-In
9:30 am–10:10 am		Invariance, Causality and Novel Robustness Peter Bühlmann (ETH Zürich)
10:20 am–11:00 am		Generalization Bounds for Uniformly Stable Algorithms Vitaly Feldman (Google)
11:10 am–11:30 am		Break
11:30 am–12:10 pm		Orthogonal Machine Learning: Power and Limitations Lester Mackey (Microsoft Research)
12:20 pm–2:00 pm		Lunch
2:00 pm–2:40 pm		Some Problems of Robust High-dimensional Statistics Gilad Lerman (University of Minnesota)
2:50 pm–3:30 pm		TAP Free Energy, Spin Glasses, and Variational Inference Zhou Fan (Yale University)
3:40 pm–4:00 pm		Break
4:00 pm–4:40 pm		A Modern Maximum-Likelihood Theory for High-Dimensional Logistic Regression Pragya Sur (Stanford University)
4:50 pm–5:30 pm		Robustness in High-Dimensional Inference Tasks Jelena Bradic (UC San Diego)

Wednesday, October 31st, 2018
9:00 am–9:30 am		Coffee and Check-In
9:30 am–10:10 am		Controlling FDR While Highlighting Selected Discoveries Chiara Sabatti (Stanford University)
10:20 am–11:00 am		The Robustness of Controlling the False Discovery Rate Weijie Su (University of Pennsylvania)
11:10 am–11:30 am		Break
11:30 am–12:10 pm		A Flexible Framework for Hypothesis Testing in High-Dimensions Adel Javanmard (University of Southern California)
12:20 pm–2:00 pm		Lunch
2:00 pm–3:00 pm		Lightning Talks

Thursday, November 1st, 2018
9:00 am–9:30 am		Coffee and Check-In
9:30 am–10:10 am		Robust Sparse Covariance Estimation by Thresholding Tyler's M-estimator Boaz Nadler (Weizmann Institute of Science)
10:20 am–11:00 am		Sub-Gaussian Mean Estimation in Polynomial Time Samuel Hopkins (UC Berkeley)
11:10 am–11:30 am		Break
11:30 am–12:10 pm		Robust Estimation and Generative Adversarial Nets Chao Gao (University of Chicago)
12:20 pm–2:00 pm		Lunch
2:00 pm–2:40 pm		Can Non-Convex Optimization be Robust? Rong Ge (Duke University)
2:50 pm–3:30 pm		Semi-Random Models and Robustness in Unsupervised Learning Aravindan Vijayaraghavan (Northwestern University)
3:40 pm–4:00 pm		Break
4:00 pm–4:40 pm		Optimally Weighted PCA for High-Dimensional Heteroscedastic Data Laura Balzano (University of Michigan)
4:50 pm–5:30 pm		How Many Directions Determine a Shape: A VC Theory for Modulii Spaces of Shapes Sayan Mukherjee (Duke University)

Friday, November 2nd, 2018
9:00 am–9:30 am		Coffee and Check-In
9:30 am–10:10 am		Scale Calibration for High-Dimensional Robust Regression Po-Ling Loh (University of Wisconsin, Madison)
10:20 am–11:00 am		k-means and k-medians under Dimension Reduction Yury Makarychev (Toyota Technological Institute at Chicago)
11:10 am–11:30 am		Break
11:30 am–12:10 pm		Efficient Profile Maximum Likelihood for Universal Symmetric Property Estimation Moses Charikar (Stanford University)
12:20 pm–1:00 pm		Realizing Robustness Gautam Kamath (Massachusetts Institute of Technology)