← Authors

Lingjiong Zhu

15 papers · 2019–2025 · 5 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (24) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (15) 🌍 Conference Polyglot (5) πŸƒ Academic Marathon (6) πŸŒ‰ Interdisciplinary Bridge 🀝 Dynamic Duo (13) πŸ—ƒοΈ Keyword Collector (63) ⚑ Prolific Year (5) πŸ’Ž Century Club (15) πŸ”₯ Unstoppable (7)

Conferences

ICML (5) JMLR (4) NIPS (4) AISTATS (1) ALT (1)

Top co-authors

Mert Gurbuzbalaban (13) Umut Simsekli (8) Xuefeng GAO (4) Anant Raj (3) Alexander Camuto (2) Murat A Erdogdu (2) Yuanhan Hu (2) Hoang M. Nguyen (1) Asuman Ozdaglar (1) Bugra Can (1)

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