conftrace_

heavy-tailed noise

23 papers

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Co-occurring keywords

stochastic gradient descent (1091) stochastic optimization (1060) gradient clipping (54) regret bound (1926) non-convex optimization (547) sub-gaussian noise (10) convergence rate (607) linear bandit (124) heavy-tailed distribution (98) complexity bound (50)

Papers

Error estimation and adaptive tuning for unregularized robust M-estimator JMLR 2025
Error Analysis Affected by Heavy-Tailed Gradients for Non-Convex Pairwise Stochastic Gradient Descent AAAI 2025
Revisiting Gradient Normalization and Clipping for Nonconvex SGD under Heavy-Tailed Noise: Necessity, Sufficiency, and Acceleration JMLR 2025
Safe Online Convex Optimization with Heavy-Tailed Observation Noises AAAI 2025
General Tail Bounds for Non-Smooth Stochastic Mirror Descent AISTATS 2024
Revisiting the Noise Model of Stochastic Gradient Descent AISTATS 2024
Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization Problems AISTATS 2024
Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise COLT 2023
Beyond Sub-Gaussian Noises: Sharp Concentration Analysis for Stochastic Gradient Descent JMLR 2022
Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise NIPS 2022
Convergence Rates of Stochastic Gradient Descent under Infinite Noise Variance NIPS 2021
Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs NIPS 2021
Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections ICML 2021
Why are Adaptive Methods Good for Attention Models? NIPS 2020
Stochastic Optimization with Heavy-Tailed Noise via Accelerated Gradient Clipping NIPS 2020
Robustness Analysis of Non-Convex Stochastic Gradient Descent using Biased Expectations NIPS 2020
Estimating Rank-One Spikes from Heavy-Tailed Noise via Self-Avoiding Walks NIPS 2020
Hausdorff Dimension, Heavy Tails, and Generalization in Neural Networks NIPS 2020
Learning with Non-Convex Truncated Losses by SGD UAI 2019
Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for Non-Convex Optimization ICML 2019
Bayesian Optimization under Heavy-tailed Payoffs NIPS 2019
Regularized Modal Regression with Applications in Cognitive Impairment Prediction NIPS 2017
No-Regret Algorithms for Heavy-Tailed Linear Bandits ICML 2016