Toggle navigation
Tengyuan Liang
Bio
Research
Teaching
Talks
Optimization and Control (math.OC)
Randomization Inference When N Equals One
High-Dimensional Asymptotics of Langevin Dynamics in Spiked Matrix Models
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
Training Neural Networks as Learning Data-adaptive Kernels: Provable Representation and Approximation Benefits
Statistical Inference for the Population Landscape via Moment Adjusted Stochastic Gradients
Interaction Matters: A Note on Non-asymptotic Local Convergence of Generative Adversarial Networks
Local Optimality and Generalization Guarantees for the Langevin Algorithm via Empirical Metastability
Escaping the Local Minima via Simulated Annealing: Optimization of Approximately Convex Functions
×
Cite