Schedule

2:30 pm3:00 pm
Registration & Welcome
Opening Remarks: Matias Cattaneo
3:00 pm3:40 pm
Isaiah Andrews
Bootstrap Diagnostics for Irregular Estimators
3:40 pm4:20 pm
Michael Mahoney
Model Selection And Ensembling When There Are More Parameters Than Data
4:20 pm4:40 pm
4:40 pm5:20 pm
Yury Polyanskiy
Likelihood-free hypothesis testing
5:20 pm6:00 pm
Jerry Li
A Theory for Quantum Learning in the NISQ Era
8:30 am9:00 am
9:00 am9:40 am
Cynthia Rush
The out-of-sample prediction error of the square-root lasso and related estimators
9:40 am10:20 am
Yue Lu
Understanding the Universality Phenomenon in High-Dimensional Estimation and Learning: Some Recent Progress
10:20 am10:40 am
10:40 am11:20 am
Yuting Wei
Approximate message passing: A non-asymptotic framework and beyond
11:20 am12:00 pm
Junwei Lu
Ranking Inference for Human Feedback Tuning in Large Language Models
12:00 pm1:30 pm
1:30 pm
2:00 pm2:40 pm
Jacob Bien
Generalized Data Thinning Using Sufficient Statistics
2:40 pm3:20 pm
Elynn Chen
Transferred Q-learning
3:20 pm3:40 pm
3:40 pm4:20 pm
Ilias Diakonikolas
Provably learning neural networks
4:20 pm5:00 pm
Cris Moore
Tensor Networks, Phase transitions, and Algorithms
5:00 pm
Coffee Break & Conference Conclusion
Closing Remarks: Jianqing Fan