Statistical Learning
Towards Robust and Expressive Whole-body Human Pose and Shape Estimation Hui En Pang
Whole-body pose and shape estimation aims to jointly predict different behaviors (e.g., pose, hand gesture, facial expression) of the entire human body from a
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms
Understanding generalization in deep learning has been one of the major challenges in statistical learning theory over the last decade.
Supplementary Material for AutoMS Automatic Model Selection for Novelty
It is worth mentioning that SRS is guaranteed with FDR control for any given detector.
Understanding Benign Overfitting in Gradient-based Meta Learning
Meta learning has demonstrated tremendous success in few-shot learning with limited supervised data. In those settings, the meta model is usually overparameterized.
Understanding Benign Overfitting in Gradient-based Meta Learning
Meta learning has demonstrated tremendous success in few-shot learning with limited supervised data. In those settings, the meta model is usually overparameterized.
Structured Semidefinite Programming for Recovering Structured Preconditioners Arun Jambulapati Simons Institute
We develop a general framework for finding approximately-optimal preconditioners for solving linear systems.