Events List

Statistical Learning and Matching Markets

Thursday, February 17, 2022 - 11:00 to 12:00

Speaker Xiaowu Dai, Postdoctoral Researcher, Department of Economics and EECS, University of California Berkeley

Event Type Statistics Seminar

Location Zoom

Observational Data with a Continuous Exposure: Study Design and Data Analysis

Tuesday, February 15, 2022 - 11:00 to 12:00

Speaker Bo Zhang, PhD student, Department of Statistics and Data Science, The Wharton School, University of Pennsylvania

Event Type Statistics Seminar

Location Zoom

Nonparametric Empirical Bayes Inference

Friday, February 11, 2022 - 11:00 to 12:00

Speaker Nikolaos Ignatiadis, PhD Student, Department of Statistics, Stanford University

Event Type Statistics Seminar

Location Zoom

The folded concave Laplacian spectral penalty learns block diagonal sparsity patterns with the strong oracle property

Tuesday, February 8, 2022 - 11:00 to 12:00

Speaker Iain Carmichael, Postdoctoral Researcher, Harvard Medical School

Event Type Statistics Seminar

Location Zoom

Valid Inference After Hierarchical Clustering

Thursday, February 3, 2022 - 11:00 to 12:00

Speaker Lucy Gao, Assistant Professor, Department of Statistics and Actuarial Science, University of Waterloo

Event Type Statistics Seminar

Location Zoom

A simple measure of conditional dependence

Tuesday, February 1, 2022 - 11:00 to 12:00

Speaker Mona Azadkia, Postdoctoral Researcher, Seminar for Statistics, Department of Mathematics, ETH Zürich

Event Type Statistics Seminar

Location Zoom

Some probability “paradoxes” to warm up your winter

Tuesday, November 30, 2021 - 11:00 to 12:00

Speaker Mark Holmes, UBC Mathematics Visiting Professor; Professor of Probability Theory and Stochastic Processes, School of Mathematics and Statistics, University of Melbourne

Event Type Statistics Seminar

Location Zoom / ESB 4192

Semiparametric inference under a density ratio model

Tuesday, November 23, 2021 - 11:00 to 12:00

Speaker Archer Gong Zhang, UBC Statistics PhD student

Event Type Graduate Student Seminar

Location Zoom / ESB 4192

Kriging Performance Without Kriging Complexity

Tuesday, November 16, 2021 - 11:00 to 12:00

Speaker Donald R. Jones, Department of Aerospace Engineering, University of Michigan

Event Type Statistics Seminar

Location Zoom / ESB 4192

Model Projections in Model Space (MPMS): A geometric interpretation of the AIC and estimating the distance between the generating process and the best approximating model

Tuesday, November 9, 2021 - 11:00 to 12:00

Speaker José Miguel Ponciano, Department of Biology, University of Florida

Event Type Statistics Seminar

Location Zoom

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Statistical Learning and Matching Markets

Observational Data with a Continuous Exposure: Study Design and Data Analysis

Nonparametric Empirical Bayes Inference

The folded concave Laplacian spectral penalty learns block diagonal sparsity patterns with the strong oracle property

Valid Inference After Hierarchical Clustering

A simple measure of conditional dependence

Some probability “paradoxes” to warm up your winter

Semiparametric inference under a density ratio model

Kriging Performance Without Kriging Complexity

Model Projections in Model Space (MPMS): A geometric interpretation of the AIC and estimating the distance between the generating process and the best approximating model

Pages

News & Events

News & Events

Subscribe to email list

User menu

You are here

Events List

Statistical Learning and Matching Markets

Observational Data with a Continuous Exposure: Study Design and Data Analysis

Nonparametric Empirical Bayes Inference

The folded concave Laplacian spectral penalty learns block diagonal sparsity patterns with the strong oracle property

Valid Inference After Hierarchical Clustering

A simple measure of conditional dependence

Some probability “paradoxes” to warm up your winter

Semiparametric inference under a density ratio model

Kriging Performance Without Kriging Complexity

Model Projections in Model Space (MPMS): A geometric interpretation of the AIC and estimating the distance between the generating process and the best approximating model

Pages