Lexing Ying
20 papers · 2020–2025 · 7 conferences · across top CS/AI conferences
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ICLR (6)
ICML (4)
NIPS (4)
AISTATS (3)
AAAI (1)
JMLR (1)
UAI (1)
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Research topics
Keywords
data distribution
(2)
distribution shift
(2)
stochastic gradient descent
(2)
gradient descent
(2)
global convergence
(1)
minimax optimality
(1)
adversarial robustness
(1)
regret minimization
(1)
multi-label classification
(1)
monte carlo simulation
(1)
loss landscape
(1)
nonparametric regression
(1)
nonparametric estimation
(1)
generalization error
(1)
kernel regression
(1)
variance reduction
(1)
neural network optimization
(1)
learning rate decay
(1)
pareto optimality
(1)
online learning
(1)
Papers
How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework
ICLR 2025
COS-DPO: Conditioned One-Shot Multi-Objective Fine-Tuning Framework
UAI 2025
Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty
ICML 2024
Statistical Spatially Inhomogeneous Diffusion Inference
AAAI 2024
Accelerating Sinkhorn algorithm with sparse Newton iterations
ICLR 2024
Multi-objective Optimization via Wasserstein-Fisher-Rao Gradient Flow
AISTATS 2024
Understanding the Generalization Benefits of Late Learning Rate Decay
AISTATS 2024
Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexity
NIPS 2024
Continuous-in-time Limit for Bayesian Bandits
JMLR 2023
When can Regression-Adjusted Control Variate Help? Rare Events, Sobolev Embedding and Minimax Optimality
NIPS 2023
Minimax Optimal Kernel Operator Learning via Multilevel Training
ICLR 2023
Machine Learning For Elliptic PDEs: Fast Rate Generalization Bound, Neural Scaling Law and Minimax Optimality
ICLR 2022
Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent
NIPS 2022
How to Learn when Data Gradually Reacts to Your Model
AISTATS 2022
Provably convergent quasistatic dynamics for mean-field two-player zero-sum games
ICLR 2022
How to Learn when Data Reacts to Your Model: Performative Gradient Descent
ICML 2021
Top-k eXtreme Contextual Bandits with Arm Hierarchy
ICML 2021
On Linear Stability of SGD and Input-Smoothness of Neural Networks
NIPS 2021
Why resampling outperforms reweighting for correcting sampling bias with stochastic gradients
ICLR 2021
A Mean Field Analysis Of Deep ResNet And Beyond: Towards Provably Optimization Via Overparameterization From Depth
ICML 2020