Skip to content
conftrace_

heavy-tailed noise

47 papers

Papers

High Probability Convergence Guarantees of Stochastic Gradient Descent Ascent in Structured Nonconvex Min-Max Games COLT 2026 Robust and Computationally Efficient Linear Contextual Bandits under Adversarial Corruption and Heavy-Tailed Noise UAI 2026 The Convergence Behavior of Adam under Heavy-Tailed Noise UAI 2026 Tight Long-Term Tail Decay of (Clipped) SGD in Non-Convex Optimization COLT 2026 Vanilla SGD with Momentum Survives Heavy-Tailed Noise: Convergence Analysis without Gradient Clipping or Normalization UAI 2026 Clipping Improves Adam-Norm and AdaGrad-Norm when the Noise Is Heavy-Tailed ICML 2025 Corruption-Robust Variance-aware Algorithms for Generalized Linear Bandits under Heavy-tailed Rewards UAI 2025 Efficient Distributed Optimization under Heavy-Tailed Noise ICML 2025 Error Analysis Affected by Heavy-Tailed Gradients for Non-Convex Pairwise Stochastic Gradient Descent AAAI 2025 Error estimation and adaptive tuning for unregularized robust M-estimator JMLR 2025 From Gradient Clipping to Normalization for Heavy Tailed SGD AISTATS 2025 Heavy-Tailed Linear Bandits: Huber Regression with One-Pass Update ICML 2025 High-probability Convergence Bounds for Online Nonlinear Stochastic Gradient Descent under Heavy-tailed Noise AISTATS 2025 MindFlayer SGD: Efficient Parallel SGD in the Presence of Heterogeneous and Random Worker Compute Times UAI 2025 Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping ICLR 2025 Outlier-Robust Linear System Identification Under Heavy-Tailed Noise L4DC 2025 Revisiting Gradient Normalization and Clipping for Nonconvex SGD under Heavy-Tailed Noise: Necessity, Sufficiency, and Acceleration JMLR 2025 Robust Gradient Descent for Phase Retrieval AISTATS 2025 Safe Online Convex Optimization with Heavy-Tailed Observation Noises AAAI 2025 Unbiased and Sign Compression in Distributed Learning: Comparing Noise Resilience via SDEs AISTATS 2025 Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization Problems AISTATS 2024 General Tail Bounds for Non-Smooth Stochastic Mirror Descent AISTATS 2024 Implicit Compressibility of Overparametrized Neural Networks Trained with Heavy-Tailed SGD ICML 2024 Optimal Kernel Quantile Learning with Random Features ICML 2024 Revisiting the Noise Model of Stochastic Gradient Descent AISTATS 2024