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Tengyuan Liang
Bio
Learning (cs.LG)
Reversible Gromov-Monge Sampler for Simulation-Based Inference
Interpolating Classifiers Make Few Mistakes
Blessings and Curses of Covariate Shifts: Adversarial Learning Dynamics, Directional Convergence, and Equilibria
Online Learning to Transport via the Minimal Selection Principle
Universal Prediction Band via Semi-Definite Programming
A Precise High-Dimensional Asymptotic Theory for Boosting and Minimum-L1-Norm Interpolated Classifiers
Mehler’s Formula, Branching Process, and Compositional Kernels of Deep Neural Networks
How Well Generative Adversarial Networks Learn Distributions
Deep Neural Networks for Estimation and Inference
Training Neural Networks as Learning Data-adaptive Kernels: Provable Representation and Approximation Benefits
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