Lingjiong Zhu
15 papers · 2019–2025 · 5 conferences · across top CS/AI conferences
Achievements
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🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (6) 🌍 Conference Polyglot (5) 🐝 Cross-Pollinator (15)
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Conferences
ICML (5)
JMLR (4)
NIPS (4)
AISTATS (1)
ALT (1)
Top co-authors
Keywords
stochastic gradient descent
(11)
langevin dynamics
(4)
wasserstein distance
(4)
algorithmic stability
(3)
generalization bound
(3)
markov chain monte carlo
(3)
non-convex optimization
(2)
generalization error
(2)
heavy-tailed noise
(2)
heavy-tailed distribution
(2)
stochastic gradient
(2)
stochastic differential equation
(2)
bayesian inference
(2)
natural gradient
(1)
neural network optimization
(1)
bayesian learning
(1)
decentralized optimization
(1)
accelerated gradient
(1)
distributed learning
(1)
polyak-ruppert averaging
(1)
Papers
Wasserstein Convergence Guarantees for a General Class of Score-Based Generative Models
JMLR 2025
Convergence Analysis for General Probability Flow ODEs of Diffusion Models in Wasserstein Distances
AISTATS 2025
Penalized Overdamped and Underdamped Langevin Monte Carlo Algorithms for Constrained Sampling
JMLR 2024
Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions
ICML 2023
Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent
NIPS 2023
Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares
ALT 2023
Robust Distributed Accelerated Stochastic Gradient Methods for Multi-Agent Networks
JMLR 2022
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms
NIPS 2021
Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections
ICML 2021
The Heavy-Tail Phenomenon in SGD
ICML 2021
Convergence Rates of Stochastic Gradient Descent under Infinite Noise Variance
NIPS 2021
Decentralized Stochastic Gradient Langevin Dynamics and Hamiltonian Monte Carlo
JMLR 2021
Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise
ICML 2020
Breaking Reversibility Accelerates Langevin Dynamics for Non-Convex Optimization
NIPS 2020
Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances
ICML 2019