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. 2503.19939
  4. Cited By
Continual Learning With Quasi-Newton Methods

Continual Learning With Quasi-Newton Methods

IEEE Access (IEEE Access), 2021
25 March 2025
Steven Vander Eeckt
Hugo Van hamme
    CLLBDL
ArXiv (abs)PDFHTMLGithub (1★)

Papers citing "Continual Learning With Quasi-Newton Methods"

44 / 44 papers shown
A Comprehensive Survey of Continual Learning: Theory, Method and
  Application
A Comprehensive Survey of Continual Learning: Theory, Method and ApplicationIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Liyuan Wang
Xingxing Zhang
Hang Su
Jun Zhu
KELMCLL
956
1,280
0
31 Jan 2023
Rehearsal revealed: The limits and merits of revisiting samples in
  continual learning
Rehearsal revealed: The limits and merits of revisiting samples in continual learningIEEE International Conference on Computer Vision (ICCV), 2021
Eli Verwimp
Matthias De Lange
Tinne Tuytelaars
CLL
240
120
0
15 Apr 2021
Gradient Projection Memory for Continual Learning
Gradient Projection Memory for Continual LearningInternational Conference on Learning Representations (ICLR), 2021
Gobinda Saha
Isha Garg
Kaushik Roy
VLMCLL
347
402
0
17 Mar 2021
Training Networks in Null Space of Feature Covariance for Continual
  Learning
Training Networks in Null Space of Feature Covariance for Continual LearningComputer Vision and Pattern Recognition (CVPR), 2021
Shipeng Wang
Xiaorong Li
Jian Sun
Zongben Xu
CLL
416
208
0
12 Mar 2021
Learning Invariant Representation for Continual Learning
Learning Invariant Representation for Continual Learning
Ghada Sokar
Decebal Constantin Mocanu
Mykola Pechenizkiy
BDLCLL
166
16
0
15 Jan 2021
Gradient Episodic Memory with a Soft Constraint for Continual Learning
Gradient Episodic Memory with a Soft Constraint for Continual Learning
Guannan Hu
Wu Zhang
Hu Ding
Wenhao Zhu
CLL
135
15
0
16 Nov 2020
Continual Learning in Low-rank Orthogonal Subspaces
Continual Learning in Low-rank Orthogonal Subspaces
Arslan Chaudhry
Naeemullah Khan
P. Dokania
Juil Sock
CLL
393
161
0
22 Oct 2020
Natural Way to Overcome the Catastrophic Forgetting in Neural Networks
Natural Way to Overcome the Catastrophic Forgetting in Neural Networks
Alexey Kutalev
CLL
159
8
0
27 Apr 2020
Continual Learning with Extended Kronecker-factored Approximate
  Curvature
Continual Learning with Extended Kronecker-factored Approximate CurvatureComputer Vision and Pattern Recognition (CVPR), 2020
Janghyeon Lee
H. Hong
Donggyu Joo
Junmo Kim
CLL
256
71
0
16 Apr 2020
Dark Experience for General Continual Learning: a Strong, Simple
  Baseline
Dark Experience for General Continual Learning: a Strong, Simple BaselineNeural Information Processing Systems (NeurIPS), 2020
Pietro Buzzega
Matteo Boschini
Angelo Porrello
Davide Abati
Simone Calderara
BDLCLL
635
1,260
0
15 Apr 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library
PyTorch: An Imperative Style, High-Performance Deep Learning LibraryNeural Information Processing Systems (NeurIPS), 2019
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
1.2K
51,304
0
03 Dec 2019
Orthogonal Gradient Descent for Continual Learning
Orthogonal Gradient Descent for Continual LearningInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Mehrdad Farajtabar
Navid Azizan
Alex Mott
Ang Li
CLL
763
485
0
15 Oct 2019
A Unifying Bayesian View of Continual Learning
A Unifying Bayesian View of Continual Learning
Sebastian Farquhar
Y. Gal
BDLCLL
177
80
0
18 Feb 2019
Quasi-Newton Methods for Machine Learning: Forget the Past, Just Sample
Quasi-Newton Methods for Machine Learning: Forget the Past, Just Sample
A. Berahas
Majid Jahani
Peter Richtárik
Martin Takávc
424
51
0
28 Jan 2019
Efficient Lifelong Learning with A-GEM
Efficient Lifelong Learning with A-GEM
Arslan Chaudhry
MarcÁurelio Ranzato
Marcus Rohrbach
Mohamed Elhoseiny
CLL
1.1K
1,719
0
02 Dec 2018
Experience Replay for Continual Learning
Experience Replay for Continual Learning
David Rolnick
Arun Ahuja
Jonathan Richard Schwarz
Timothy Lillicrap
Greg Wayne
CLL
601
1,548
0
28 Nov 2018
Learning to Learn without Forgetting by Maximizing Transfer and
  Minimizing Interference
Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference
Matthew D Riemer
Ignacio Cases
R. Ajemian
Miao Liu
Irina Rish
Y. Tu
Gerald Tesauro
CLL
583
900
0
29 Oct 2018
Continuous Learning in Single-Incremental-Task Scenarios
Continuous Learning in Single-Incremental-Task Scenarios
Davide Maltoni
Vincenzo Lomonaco
CLL
381
332
0
22 Jun 2018
Online Structured Laplace Approximations For Overcoming Catastrophic
  Forgetting
Online Structured Laplace Approximations For Overcoming Catastrophic Forgetting
H. Ritter
Aleksandar Botev
David Barber
BDLCLL
371
372
0
20 May 2018
Progress & Compress: A scalable framework for continual learning
Progress & Compress: A scalable framework for continual learning
Jonathan Richard Schwarz
Jelena Luketina
Wojciech M. Czarnecki
A. Grabska-Barwinska
Yee Whye Teh
Razvan Pascanu
R. Hadsell
CLL
644
1,010
0
16 May 2018
Rotate your Networks: Better Weight Consolidation and Less Catastrophic
  Forgetting
Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting
Xialei Liu
Marc Masana
Luis Herranz
Joost van de Weijer
Antonio M. López
Andrew D. Bagdanov
CLL
629
322
0
08 Feb 2018
Riemannian Walk for Incremental Learning: Understanding Forgetting and
  Intransigence
Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence
Arslan Chaudhry
P. Dokania
Thalaiyasingam Ajanthan
Juil Sock
CLL
710
1,358
0
30 Jan 2018
Overcoming catastrophic forgetting with hard attention to the task
Overcoming catastrophic forgetting with hard attention to the task
Joan Serrà
Dídac Surís
M. Miron
Alexandros Karatzoglou
CLL
904
1,258
0
04 Jan 2018
On Quadratic Penalties in Elastic Weight Consolidation
On Quadratic Penalties in Elastic Weight Consolidation
Ferenc Huszár
180
125
0
11 Dec 2017
Memory Aware Synapses: Learning what (not) to forget
Memory Aware Synapses: Learning what (not) to forget
Rahaf Aljundi
F. Babiloni
Mohamed Elhoseiny
Marcus Rohrbach
Tinne Tuytelaars
KELMCLL
508
1,971
0
27 Nov 2017
Variational Continual Learning
Variational Continual LearningInternational Conference on Learning Representations (ICLR), 2017
Cuong V Nguyen
Yingzhen Li
T. Bui
Richard Turner
CLLVLMBDL
641
800
0
29 Oct 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning
  Algorithms
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Han Xiao
Kashif Rasul
Roland Vollgraf
2.2K
10,439
0
25 Aug 2017
Lifelong Learning with Dynamically Expandable Networks
Lifelong Learning with Dynamically Expandable Networks
Jaehong Yoon
Eunho Yang
Jeongtae Lee
Sung Ju Hwang
CLL
1.2K
1,400
0
04 Aug 2017
Gradient Episodic Memory for Continual Learning
Gradient Episodic Memory for Continual Learning
David Lopez-Paz
MarcÁurelio Ranzato
VLMCLL
1.1K
3,331
0
26 Jun 2017
Attention Is All You Need
Attention Is All You NeedNeural Information Processing Systems (NeurIPS), 2017
Ashish Vaswani
Noam M. Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
Aidan Gomez
Lukasz Kaiser
Illia Polosukhin
3DV
8.4K
172,602
0
12 Jun 2017
Continual Learning with Deep Generative Replay
Continual Learning with Deep Generative Replay
Hanul Shin
Jung Kwon Lee
Jaehong Kim
Jiwon Kim
KELMCLL
1.0K
2,447
0
24 May 2017
CORe50: a New Dataset and Benchmark for Continuous Object Recognition
CORe50: a New Dataset and Benchmark for Continuous Object Recognition
Vincenzo Lomonaco
Davide Maltoni
417
562
0
09 May 2017
Encoder Based Lifelong Learning
Encoder Based Lifelong Learning
Amal Rannen Triki
Rahaf Aljundi
Mathew B. Blaschko
Tinne Tuytelaars
CLL
254
345
0
06 Apr 2017
Overcoming Catastrophic Forgetting by Incremental Moment Matching
Overcoming Catastrophic Forgetting by Incremental Moment Matching
Sang-Woo Lee
Jin-Hwa Kim
Jaehyun Jun
Jung-Woo Ha
Byoung-Tak Zhang
CLL
496
724
0
24 Mar 2017
PathNet: Evolution Channels Gradient Descent in Super Neural Networks
PathNet: Evolution Channels Gradient Descent in Super Neural Networks
Chrisantha Fernando
Dylan Banarse
Charles Blundell
Yori Zwols
David R Ha
Andrei A. Rusu
Alexander Pritzel
Daan Wierstra
415
952
0
30 Jan 2017
Overcoming catastrophic forgetting in neural networks
Overcoming catastrophic forgetting in neural networks
J. Kirkpatrick
Razvan Pascanu
Neil C. Rabinowitz
J. Veness
Guillaume Desjardins
...
A. Grabska-Barwinska
Demis Hassabis
Claudia Clopath
D. Kumaran
R. Hadsell
CLL
1.6K
9,526
1
02 Dec 2016
iCaRL: Incremental Classifier and Representation Learning
iCaRL: Incremental Classifier and Representation Learning
Sylvestre-Alvise Rebuffi
Alexander Kolesnikov
G. Sperl
Christoph H. Lampert
CLLOOD
923
4,633
0
23 Nov 2016
Less-forgetting Learning in Deep Neural Networks
Less-forgetting Learning in Deep Neural Networks
Heechul Jung
Jeongwoo Ju
Minju Jung
Junmo Kim
316
243
0
01 Jul 2016
Learning without Forgetting
Learning without ForgettingIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016
Zhizhong Li
Derek Hoiem
CLLOODSSL
1.5K
5,390
0
29 Jun 2016
Progressive Neural Networks
Progressive Neural Networks
Andrei A. Rusu
Neil C. Rabinowitz
Guillaume Desjardins
Hubert Soyer
J. Kirkpatrick
Koray Kavukcuoglu
Razvan Pascanu
R. Hadsell
CLLAI4CE
718
2,823
0
15 Jun 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
4.2K
226,071
0
10 Dec 2015
Optimizing Neural Networks with Kronecker-factored Approximate Curvature
Optimizing Neural Networks with Kronecker-factored Approximate Curvature
James Martens
Roger C. Grosse
ODL
1.2K
1,252
0
19 Mar 2015
Distilling the Knowledge in a Neural Network
Distilling the Knowledge in a Neural Network
Geoffrey E. Hinton
Oriol Vinyals
J. Dean
FedML
975
23,761
0
09 Mar 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic OptimizationInternational Conference on Learning Representations (ICLR), 2014
Diederik P. Kingma
Jimmy Ba
ODL
5.0K
165,267
0
22 Dec 2014
1
Page 1 of 1