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Robust and High-Dimensional Statistics
Program
Foundations of Data Science
Location
Calvin Lab Auditorium
Date
Monday, Oct. 29
–
Friday, Nov. 2, 2018
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Click on the titles of individual talks for abstract, slides and archived video.
Monday, Oct. 29, 2018
9
–
9:20 a.m.
Coffee and Check-In
9:20
–
9:30 a.m.
Opening Remarks
9:30
–
10:10 a.m.
Robust List Decoding of Spherical Gaussians
Daniel Kane (UC San Diego)
10:20
–
11 a.m.
Mixture Models, Robustness, and Sum of Squares Proofs
Jerry Li (Microsoft Research)
11:10
–
11:30 a.m.
Break
11:30 a.m.
–
12:10 p.m.
Computational-Statistical Tradeoffs in Robust High-Dimensional Estimation
Ilias Diakonikolas (University of Wisconsin-Madison)
12:20
–
2 p.m.
Lunch
2
–
2:40 p.m.
Efficient Algorithms for Outlier-Robust Regression
Adam Klivans (University of Texas, Austin)
2:50
–
3:30 p.m.
Detecting Weak Signals via Hypothesis Testing
Ravi Kannan (Simons Institute, UC Berkeley)
3:40
–
4 p.m.
Break
4
–
4:40 p.m.
On Using Graph Distances to Estimate Euclidean and Related Distances
Ery Arias-Castro (UC San Diego)
4:50
–
5:30 p.m.
The Importance of Better Models in Stochastic Optimization - Robustness, Fast Convergence, and Optimality
John Duchi (Stanford University)
5:40 p.m. PT
Reception
Tuesday, Oct. 30, 2018
9
–
9:30 a.m.
Coffee and Check-In
9:30
–
10:10 a.m.
Invariance, Causality and Novel Robustness
Peter Bühlmann (ETH Zürich)
10:20
–
11 a.m.
Generalization Bounds for Uniformly Stable Algorithms
Vitaly Feldman (Apple)
11:10
–
11:30 a.m.
Break
11:30 a.m.
–
12:10 p.m.
Orthogonal Machine Learning: Power and Limitations
Lester Mackey (Microsoft Research)
12:20
–
2 p.m.
Lunch
2
–
2:40 p.m.
Some Problems of Robust High-dimensional Statistics
Gilad Lerman (University of Minnesota)
2:50
–
3:30 p.m.
TAP Free Energy, Spin Glasses, and Variational Inference
Zhou Fan (Yale University)
3:40
–
4 p.m.
Break
4
–
4:40 p.m.
A Modern Maximum-Likelihood Theory for High-Dimensional Logistic Regression
Pragya Sur (Stanford University)
4:50
–
5:30 p.m.
Robustness in High-Dimensional Inference Tasks
Jelena Bradic (UC San Diego)
Wednesday, Oct. 31, 2018
9
–
9:30 a.m.
Coffee and Check-In
9:30
–
10:10 a.m.
Controlling FDR While Highlighting Selected Discoveries
Chiara Sabatti (Stanford University)
10:20
–
11 a.m.
The Robustness of Controlling the False Discovery Rate
Weijie Su (University of Pennsylvania)
11:10
–
11:30 a.m.
Break
11:30 a.m.
–
12:10 p.m.
A Flexible Framework for Hypothesis Testing in High-Dimensions
Adel Javanmard (University of Southern California (USC))
12:20
–
2 p.m.
Lunch
2
–
3 p.m.
Lightning Talks
Thursday, Nov. 1, 2018
9
–
9:30 a.m.
Coffee and Check-In
9:30
–
10:10 a.m.
Robust Sparse Covariance Estimation by Thresholding Tyler's M-estimator
Boaz Nadler (Weizmann Institute)
10:20
–
11 a.m.
Sub-Gaussian Mean Estimation in Polynomial Time
Samuel Hopkins (UC Berkeley)
11:10
–
11:30 a.m.
Break
11:30 a.m.
–
12:10 p.m.
Robust Estimation and Generative Adversarial Nets
Chao Gao (University of Chicago)
12:20
–
2 p.m.
Lunch
2
–
2:40 p.m.
Can Non-Convex Optimization be Robust?
Rong Ge (Duke University)
2:50
–
3:30 p.m.
Semi-Random Models and Robustness in Unsupervised Learning
Aravindan Vijayaraghavan (Northwestern University)
3:40
–
4 p.m.
Break
4
–
4:40 p.m.
Optimally Weighted PCA for High-Dimensional Heteroscedastic Data
Laura Balzano (University of Michigan)
4:50
–
5:30 p.m.
How Many Directions Determine a Shape: A VC Theory for Modulii Spaces of Shapes
Sayan Mukherjee (Duke University)
Friday, Nov. 2, 2018
9
–
9:30 a.m.
Coffee and Check-In
9:30
–
10:10 a.m.
Scale Calibration for High-Dimensional Robust Regression
Po-Ling Loh (University of Wisconsin, Madison)
10:20
–
11 a.m.
k-means and k-medians under Dimension Reduction
Yury Makarychev (Toyota Technological Institute at Chicago)
11:10
–
11:30 a.m.
Break
11:30 a.m.
–
12:10 p.m.
Efficient Profile Maximum Likelihood for Universal Symmetric Property Estimation
Moses Charikar (Stanford University)
12:20
–
1 p.m.
Realizing Robustness
Gautam Kamath (Massachusetts Institute of Technology)
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