Tengyuan Liang
12 papers · 2015–2024 · 4 venues · across top CS/AI venues
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Machine Learning
(12)
Optimization & Theory · Machine Learning
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Mathematics & Optimization
(3)
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statistical learning
(3)
generalization bound
(2)
generative adversarial network
(2)
reproducing kernel hilbert space
(2)
empirical risk minimization
(2)
non-convex optimization
(2)
generalization guarantee
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online learning
(2)
convex optimization
(1)
nash equilibrium
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stochastic optimization
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equilibrium learning
(1)
covariate shift
(1)
kernel matrix
(1)
community detection
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mean-field approximation
(1)
rademacher complexity
(1)
optimal transport
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generalization error
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simulated annealing
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Papers
Blessings and Curses of Covariate Shifts: Adversarial Learning Dynamics, Directional Convergence, and Equilibria
JMLR 2024
Interpolating Classifiers Make Few Mistakes
JMLR 2023
Online Learning to Transport via the Minimal Selection Principle
COLT 2022
How Well Generative Adversarial Networks Learn Distributions
JMLR 2021
On the Multiple Descent of Minimum-Norm Interpolants and Restricted Lower Isometry of Kernels
COLT 2020
Weighted Message Passing and Minimum Energy Flow for Heterogeneous Stochastic Block Models with Side Information
JMLR 2020
Fisher-Rao Metric, Geometry, and Complexity of Neural Networks
AISTATS 2019
Interaction Matters: A Note on Non-asymptotic Local Convergence of Generative Adversarial Networks
AISTATS 2019
Local Optimality and Generalization Guarantees for the Langevin Algorithm via Empirical Metastability
COLT 2018
Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression under RIP
ICML 2017
Escaping the Local Minima via Simulated Annealing: Optimization of Approximately Convex Functions
COLT 2015
Learning with Square Loss: Localization through Offset Rademacher Complexity
COLT 2015