ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2301.11885
  4. Cited By
Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions
v1v2 (latest)

Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions

International Conference on Machine Learning (ICML), 2023
27 January 2023
Anant Raj
Lingjiong Zhu
Mert Gurbuzbalaban
Umut Simsekli
ArXiv (abs)PDFHTML

Papers citing "Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions"

13 / 13 papers shown
Rényi Differential Privacy for Heavy-Tailed SDEs via Fractional Poincaré Inequalities
Rényi Differential Privacy for Heavy-Tailed SDEs via Fractional Poincaré Inequalities
Benjamin Dupuis
Mert Gurbuzbalaban
Umut Simsekli
Jian Wang
Sinan Yildirim
Lingjiong Zhu
81
0
0
19 Nov 2025
Learning Rate Should Scale Inversely with High-Order Data Moments in High-Dimensional Online Independent Component Analysis
Learning Rate Should Scale Inversely with High-Order Data Moments in High-Dimensional Online Independent Component Analysis
M. Oguzhan Gultekin
Samet Demir
Zafer Dogan
112
0
0
18 Sep 2025
Understanding the Generalization Error of Markov algorithms through Poissonization
Understanding the Generalization Error of Markov algorithms through Poissonization
Benjamin Dupuis
Maxime Haddouche
George Deligiannidis
Umut Simsekli
285
1
0
11 Feb 2025
Limit Theorems for Stochastic Gradient Descent with Infinite Variance
Limit Theorems for Stochastic Gradient Descent with Infinite Variance
Jose H. Blanchet
Aleksandar Mijatović
Wenhao Yang
402
1
0
21 Oct 2024
From Spikes to Heavy Tails: Unveiling the Spectral Evolution of Neural Networks
From Spikes to Heavy Tails: Unveiling the Spectral Evolution of Neural Networks
Vignesh Kothapalli
Tianyu Pang
Shenyang Deng
Zongmin Liu
Yaoqing Yang
367
4
0
07 Jun 2024
Emergence of heavy tails in homogenized stochastic gradient descent
Emergence of heavy tails in homogenized stochastic gradient descent
Zhe Jiao
Martin Keller-Ressel
164
3
0
02 Feb 2024
From Mutual Information to Expected Dynamics: New Generalization Bounds
  for Heavy-Tailed SGD
From Mutual Information to Expected Dynamics: New Generalization Bounds for Heavy-Tailed SGD
Benjamin Dupuis
Paul Viallard
237
5
0
01 Dec 2023
Temperature Balancing, Layer-wise Weight Analysis, and Neural Network
  Training
Temperature Balancing, Layer-wise Weight Analysis, and Neural Network TrainingNeural Information Processing Systems (NeurIPS), 2023
Yefan Zhou
Tianyu Pang
Keqin Liu
Charles H. Martin
Michael W. Mahoney
Yaoqing Yang
387
14
0
01 Dec 2023
Approximate Heavy Tails in Offline (Multi-Pass) Stochastic Gradient
  Descent
Approximate Heavy Tails in Offline (Multi-Pass) Stochastic Gradient DescentNeural Information Processing Systems (NeurIPS), 2023
Krunoslav Lehman Pavasovic
Alain Durmus
Umut Simsekli
OffRL
161
3
0
27 Oct 2023
Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic
  Gradient Descent
Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient DescentNeural Information Processing Systems (NeurIPS), 2023
Lingjiong Zhu
Mert Gurbuzbalaban
Anant Raj
Umut Simsekli
238
7
0
20 May 2023
Efficient Sampling of Stochastic Differential Equations with Positive
  Semi-Definite Models
Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite ModelsNeural Information Processing Systems (NeurIPS), 2023
Anant Raj
Umut Simsekli
Alessandro Rudi
DiffM
384
3
0
30 Mar 2023
Cyclic and Randomized Stepsizes Invoke Heavier Tails in SGD than
  Constant Stepsize
Cyclic and Randomized Stepsizes Invoke Heavier Tails in SGD than Constant Stepsize
Mert Gurbuzbalaban
Yuanhan Hu
Umut Simsekli
Lingjiong Zhu
LRM
316
2
0
10 Feb 2023
Generalisation under gradient descent via deterministic PAC-Bayes
Generalisation under gradient descent via deterministic PAC-BayesInternational Conference on Algorithmic Learning Theory (ALT), 2022
Eugenio Clerico
Tyler Farghly
George Deligiannidis
Benjamin Guedj
Arnaud Doucet
387
6
0
06 Sep 2022
1