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High-probability Bounds for Non-Convex Stochastic Optimization with
  Heavy Tails

High-probability Bounds for Non-Convex Stochastic Optimization with Heavy Tails

28 June 2021
Ashok Cutkosky
Harsh Mehta
ArXivPDFHTML

Papers citing "High-probability Bounds for Non-Convex Stochastic Optimization with Heavy Tails"

14 / 14 papers shown
Title
Sketched Adaptive Federated Deep Learning: A Sharp Convergence Analysis
Sketched Adaptive Federated Deep Learning: A Sharp Convergence Analysis
Zhijie Chen
Qiaobo Li
A. Banerjee
FedML
37
0
0
11 Nov 2024
From Gradient Clipping to Normalization for Heavy Tailed SGD
From Gradient Clipping to Normalization for Heavy Tailed SGD
Florian Hübler
Ilyas Fatkhullin
Niao He
40
5
0
17 Oct 2024
High Probability Guarantees for Random Reshuffling
High Probability Guarantees for Random Reshuffling
Hengxu Yu
Xiao Li
45
2
0
20 Nov 2023
Demystifying the Myths and Legends of Nonconvex Convergence of SGD
Demystifying the Myths and Legends of Nonconvex Convergence of SGD
Aritra Dutta
El Houcine Bergou
Soumia Boucherouite
Nicklas Werge
M. Kandemir
Xin Li
28
0
0
19 Oct 2023
Provably Robust Temporal Difference Learning for Heavy-Tailed Rewards
Provably Robust Temporal Difference Learning for Heavy-Tailed Rewards
Semih Cayci
A. Eryilmaz
23
2
0
20 Jun 2023
Clip21: Error Feedback for Gradient Clipping
Clip21: Error Feedback for Gradient Clipping
Sarit Khirirat
Eduard A. Gorbunov
Samuel Horváth
Rustem Islamov
Fakhri Karray
Peter Richtárik
40
10
0
30 May 2023
Stochastic Nonsmooth Convex Optimization with Heavy-Tailed Noises:
  High-Probability Bound, In-Expectation Rate and Initial Distance Adaptation
Stochastic Nonsmooth Convex Optimization with Heavy-Tailed Noises: High-Probability Bound, In-Expectation Rate and Initial Distance Adaptation
Zijian Liu
Zhengyuan Zhou
30
10
0
22 Mar 2023
SGD with AdaGrad Stepsizes: Full Adaptivity with High Probability to
  Unknown Parameters, Unbounded Gradients and Affine Variance
SGD with AdaGrad Stepsizes: Full Adaptivity with High Probability to Unknown Parameters, Unbounded Gradients and Affine Variance
Amit Attia
Tomer Koren
ODL
22
26
0
17 Feb 2023
Breaking the Lower Bound with (Little) Structure: Acceleration in
  Non-Convex Stochastic Optimization with Heavy-Tailed Noise
Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise
Zijian Liu
Jiawei Zhang
Zhengyuan Zhou
34
12
0
14 Feb 2023
Near-Optimal Non-Convex Stochastic Optimization under Generalized
  Smoothness
Near-Optimal Non-Convex Stochastic Optimization under Generalized Smoothness
Zijian Liu
Srikanth Jagabathula
Zhengyuan Zhou
24
5
0
13 Feb 2023
Provable Acceleration of Heavy Ball beyond Quadratics for a Class of
  Polyak-Łojasiewicz Functions when the Non-Convexity is Averaged-Out
Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Łojasiewicz Functions when the Non-Convexity is Averaged-Out
Jun-Kun Wang
Chi-Heng Lin
Andre Wibisono
Bin Hu
35
20
0
22 Jun 2022
High Probability Bounds for a Class of Nonconvex Algorithms with AdaGrad
  Stepsize
High Probability Bounds for a Class of Nonconvex Algorithms with AdaGrad Stepsize
Ali Kavis
Kfir Y. Levy
V. Cevher
25
41
0
06 Apr 2022
Flexible risk design using bi-directional dispersion
Flexible risk design using bi-directional dispersion
Matthew J. Holland
38
6
0
28 Mar 2022
A High Probability Analysis of Adaptive SGD with Momentum
A High Probability Analysis of Adaptive SGD with Momentum
Xiaoyun Li
Francesco Orabona
92
66
0
28 Jul 2020
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