Preliminary Program Schedule
The conference will take place at the Multi-Purpose Room at the International Center unless otherwise noted in the schedule below.
Friday, November 8, 2024
9:00AM-9:30AM Breakfast
9:30AM-9:45AM Introduction
- Thomas Lee, Associate Dean, College of Letters and Science, UC Davis
- Jiming Jiang, Chair, Department of Statistics, UC Davis
9:45AM-10:45AM Keynote Session:
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Chair: Chris Drake, Professor, Department of Statistics, UC Davis
Keynote: Andrea Montanari, Professor, Department of Statistics and Department of Mathematics, Stanford University
Title: How do gradient methods solve non-convex empirical risk minimization problems?
10:45AM-11:00AM Group photo and coffee break
11:00AM-12:30PM Invited Session I: Causal Inference
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Chair: Shizhe Chen, Assistant Professor, Department of Statistics, UC Davis
- Kun Zhang, Associate Professor, Department of Philosophy, Carnegie Mellon University
- Peng Ding, Associate Professor, Department of Statistics, UC Berkeley
Speakers:
Title: Causal Representation Learning: Uncovering the Hidden World
Title: Factorial Difference-in-Differences
12:30PM-1:30PM Lunch
1:30PM-3:00PM Invited Session II: Theory of Deep Learning
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Chair: Xiucai Ding, Assistant Professor, Department of Statistics, UC Davis
- Song Mei, Assistant Professor, Department of Statistics and the Department of Electrical Engineering and Computer Sciences, UC Berkeley
- Johannes Schmidt-Hieber, Professor of Statistics, the University of Twente
Speakers:
Title: Mechanistically Demystifying Extreme-Token Phenomena in Large Language Models
Title: Statistical Guarantees for Image Classification
3:00PM-3:15PM Coffee Break
3:15PM-4:45PM Invited Session III: Statistical Learning
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Chair: Fushing Hsieh, Professor, Department of Statistics, UC Davis
- Yingying Fan, Professor of Data Sciences and Operations, University of Southern California
- Po-Ling Loh, Professor, Department of Pure Mathematics and Mathematical Statistics, University of Cambridge
Speakers:
Title: Robust Knockoffs Inference with Coupling
Title: Hypothesis testing under information constraints
5:00PM-6:15PM Poster Session/Reception
6:30PM-8:30PM Banquet
Saturday, November 9, 2024
9:30AM-10:00AM Breakfast
10:00AM-11:30AM Invited Session IV: Manifold Learning
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Chair: Xiucai Ding, Assistant Professor, Department of Statistics, UC Davis
- Naoki Saito, Professor, Department of Mathematics, UC Davis
- Rayan Saab, Professor, Department of Mathematics and Halicioglu Data Science Institute (HDSI), UC San Diego
Speakers:
Title: Multiscale Hodge Scattering Networks for Data Analysis on Simplicial Complexes
Title: Compressing Neural Networks: Sparsity, Quantization, and Low-Rank Approximation
11:30AM-1:00PM Lunch
1:00PM-3:00PM Contributed Session:
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Chair: Chris Drake, Professor, Department of Statistics, UC Davis
- Lynda Aouar, Preceptor, Department of Statistics & Data Science, Yale University
- Scott Schwartz, Assistant Professor, Department of Statistical Sciences, University of Toronto
- Jiayi Li, PhD Candidate, Department of Statistics, University of California Los Angeles
Speakers:
Title: Causal Double Machine Learning with Representative Subsampling in High-Dimensional Data
Title: Optimization in Polynomial Neural Networks: Insights from Algebraic Geometry
3:00PM-3:30PM Coffee Break
3:30PM-5:00PM Alumni Panel
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Chair: Shizhe Chen, Assistant Professor, Department of Statistics, UC Davis
- Minjie Fan ('17), Staff Machine Learning Engineer, Meta
- Xiaoyue Li ('20), Sr. Software Engineer, Google
- Yuefeng Liang ('20), Sr. Data Scientist, LinkedIn
- Xingmei Lou ('22), Data Scientist, Google
- Xiaoliu Wu ('22), Data Scientist, Google
Panelists: