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Anticorrelated Noise Injection for Improved Generalization

Anticorrelated Noise Injection for Improved Generalization

6 February 2022
Antonio Orvieto
Hans Kersting
F. Proske
Francis R. Bach
Aurélien Lucchi
ArXivPDFHTML

Papers citing "Anticorrelated Noise Injection for Improved Generalization"

33 / 33 papers shown
Title
SASSHA: Sharpness-aware Adaptive Second-order Optimization with Stable Hessian Approximation
SASSHA: Sharpness-aware Adaptive Second-order Optimization with Stable Hessian Approximation
Dahun Shin
Dongyeop Lee
Jinseok Chung
Namhoon Lee
ODL
AAML
87
0
0
25 Feb 2025
Stochastic Gradient Descent Jittering for Inverse Problems: Alleviating
  the Accuracy-Robustness Tradeoff
Stochastic Gradient Descent Jittering for Inverse Problems: Alleviating the Accuracy-Robustness Tradeoff
Peimeng Guan
Mark A. Davenport
9
0
0
18 Oct 2024
An Adaptive Stochastic Gradient Method with Non-negative Gauss-Newton
  Stepsizes
An Adaptive Stochastic Gradient Method with Non-negative Gauss-Newton Stepsizes
Antonio Orvieto
Lin Xiao
30
2
0
05 Jul 2024
Why is SAM Robust to Label Noise?
Why is SAM Robust to Label Noise?
Christina Baek
Zico Kolter
Aditi Raghunathan
NoLa
AAML
18
9
0
06 May 2024
Singular-limit analysis of gradient descent with noise injection
Singular-limit analysis of gradient descent with noise injection
Anna Shalova
André Schlichting
M. Peletier
25
1
0
18 Apr 2024
Communication-Efficient Distributed Learning with Local Immediate Error
  Compensation
Communication-Efficient Distributed Learning with Local Immediate Error Compensation
Yifei Cheng
Li Shen
Linli Xu
Xun Qian
Shiwei Wu
Yiming Zhou
Tie Zhang
Dacheng Tao
Enhong Chen
16
0
0
19 Feb 2024
Critical Influence of Overparameterization on Sharpness-aware Minimization
Critical Influence of Overparameterization on Sharpness-aware Minimization
Sungbin Shin
Dongyeop Lee
Maksym Andriushchenko
Namhoon Lee
AAML
28
1
0
29 Nov 2023
Evolutionary algorithms as an alternative to backpropagation for
  supervised training of Biophysical Neural Networks and Neural ODEs
Evolutionary algorithms as an alternative to backpropagation for supervised training of Biophysical Neural Networks and Neural ODEs
James Hazelden
Yuhan Helena Liu
Eli Shlizerman
E. Shea-Brown
23
2
0
17 Nov 2023
PAC-tuning:Fine-tuning Pretrained Language Models with PAC-driven
  Perturbed Gradient Descent
PAC-tuning:Fine-tuning Pretrained Language Models with PAC-driven Perturbed Gradient Descent
Guang-Da Liu
Zhiyu Xue
Xitong Zhang
K. Johnson
Rongrong Wang
10
5
0
26 Oct 2023
Data Optimization in Deep Learning: A Survey
Data Optimization in Deep Learning: A Survey
Ou Wu
Rujing Yao
15
1
0
25 Oct 2023
Enhancing Deep Neural Network Training Efficiency and Performance
  through Linear Prediction
Enhancing Deep Neural Network Training Efficiency and Performance through Linear Prediction
Hejie Ying
Mengmeng Song
Yaohong Tang
S. Xiao
Zimin Xiao
11
8
0
17 Oct 2023
Correlated Noise Provably Beats Independent Noise for Differentially
  Private Learning
Correlated Noise Provably Beats Independent Noise for Differentially Private Learning
Christopher A. Choquette-Choo
Krishnamurthy Dvijotham
Krishna Pillutla
Arun Ganesh
Thomas Steinke
Abhradeep Thakurta
10
13
0
10 Oct 2023
On the curvature of the loss landscape
On the curvature of the loss landscape
Alison Pouplin
Hrittik Roy
Sidak Pal Singh
Georgios Arvanitidis
16
0
0
10 Jul 2023
Edge Intelligence Over the Air: Two Faces of Interference in Federated
  Learning
Edge Intelligence Over the Air: Two Faces of Interference in Federated Learning
Zihan Chen
Howard H. Yang
Tony Q. S. Quek
27
9
0
17 Jun 2023
The Split Matters: Flat Minima Methods for Improving the Performance of
  GNNs
The Split Matters: Flat Minima Methods for Improving the Performance of GNNs
N. Lell
A. Scherp
20
1
0
15 Jun 2023
Decentralized SGD and Average-direction SAM are Asymptotically
  Equivalent
Decentralized SGD and Average-direction SAM are Asymptotically Equivalent
Tongtian Zhu
Fengxiang He
Kaixuan Chen
Mingli Song
Dacheng Tao
24
15
0
05 Jun 2023
Evolutionary Algorithms in the Light of SGD: Limit Equivalence, Minima
  Flatness, and Transfer Learning
Evolutionary Algorithms in the Light of SGD: Limit Equivalence, Minima Flatness, and Transfer Learning
Andrei Kucharavy
R. Guerraoui
Ljiljana Dolamic
20
1
0
20 May 2023
An Adaptive Policy to Employ Sharpness-Aware Minimization
An Adaptive Policy to Employ Sharpness-Aware Minimization
Weisen Jiang
Hansi Yang
Yu Zhang
James T. Kwok
AAML
69
31
0
28 Apr 2023
ELF: Federated Langevin Algorithms with Primal, Dual and Bidirectional
  Compression
ELF: Federated Langevin Algorithms with Primal, Dual and Bidirectional Compression
Avetik G. Karagulyan
Peter Richtárik
FedML
11
4
0
08 Mar 2023
The Lie-Group Bayesian Learning Rule
The Lie-Group Bayesian Learning Rule
E. M. Kıral
Thomas Möllenhoff
Mohammad Emtiyaz Khan
BDL
6
2
0
08 Mar 2023
Utility-based Perturbed Gradient Descent: An Optimizer for Continual
  Learning
Utility-based Perturbed Gradient Descent: An Optimizer for Continual Learning
Mohamed Elsayed
A. R. Mahmood
CLL
11
5
0
07 Feb 2023
Gradient Descent with Linearly Correlated Noise: Theory and Applications
  to Differential Privacy
Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy
Anastasia Koloskova
Ryan McKenna
Zachary B. Charles
Keith Rush
Brendan McMahan
17
8
0
02 Feb 2023
Implicit regularization in Heavy-ball momentum accelerated stochastic
  gradient descent
Implicit regularization in Heavy-ball momentum accelerated stochastic gradient descent
Avrajit Ghosh
He Lyu
Xitong Zhang
Rongrong Wang
21
20
0
02 Feb 2023
A Study on FGSM Adversarial Training for Neural Retrieval
A Study on FGSM Adversarial Training for Neural Retrieval
Simon Lupart
S. Clinchant
AAML
10
7
0
25 Jan 2023
Improving Generalization of Pre-trained Language Models via Stochastic
  Weight Averaging
Improving Generalization of Pre-trained Language Models via Stochastic Weight Averaging
Peng Lu
I. Kobyzev
Mehdi Rezagholizadeh
Ahmad Rashid
A. Ghodsi
Philippe Langlais
MoMe
17
8
0
12 Dec 2022
Disentangling the Mechanisms Behind Implicit Regularization in SGD
Disentangling the Mechanisms Behind Implicit Regularization in SGD
Zachary Novack
Simran Kaur
Tanya Marwah
Saurabh Garg
Zachary Chase Lipton
FedML
12
2
0
29 Nov 2022
EF21-P and Friends: Improved Theoretical Communication Complexity for
  Distributed Optimization with Bidirectional Compression
EF21-P and Friends: Improved Theoretical Communication Complexity for Distributed Optimization with Bidirectional Compression
Kaja Gruntkowska
A. Tyurin
Peter Richtárik
23
18
0
30 Sep 2022
Explicit Regularization in Overparametrized Models via Noise Injection
Explicit Regularization in Overparametrized Models via Noise Injection
Antonio Orvieto
Anant Raj
Hans Kersting
Francis R. Bach
8
25
0
09 Jun 2022
Beyond accuracy: generalization properties of bio-plausible temporal
  credit assignment rules
Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules
Yuhan Helena Liu
Arna Ghosh
Blake A. Richards
E. Shea-Brown
Guillaume Lajoie
6
9
0
02 Jun 2022
Special Properties of Gradient Descent with Large Learning Rates
Special Properties of Gradient Descent with Large Learning Rates
Amirkeivan Mohtashami
Martin Jaggi
Sebastian U. Stich
MLT
11
7
0
30 May 2022
What Happens after SGD Reaches Zero Loss? --A Mathematical Framework
What Happens after SGD Reaches Zero Loss? --A Mathematical Framework
Zhiyuan Li
Tianhao Wang
Sanjeev Arora
MLT
69
98
0
13 Oct 2021
Shift-Curvature, SGD, and Generalization
Shift-Curvature, SGD, and Generalization
Arwen V. Bradley
C. Gomez-Uribe
Manish Reddy Vuyyuru
12
2
0
21 Aug 2021
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
273
2,696
0
15 Sep 2016
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