ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2403.09066
  4. Cited By
Hyperparameters in Continual Learning: A Reality Check
v1v2v3v4 (latest)

Hyperparameters in Continual Learning: A Reality Check

14 March 2024
Sungmin Cha
Kyunghyun Cho
    CLL
ArXiv (abs)PDFHTML

Papers citing "Hyperparameters in Continual Learning: A Reality Check"

50 / 56 papers shown
Title
Learning Equi-angular Representations for Online Continual Learning
Learning Equi-angular Representations for Online Continual Learning
Minhyuk Seo
Hyun-woo Koh
Wonje Jeung
Minjae Lee
San Kim
Hankook Lee
Sungjun Cho
Sungik Choi
Hyunwoo Kim
Jonghyun Choi
CLL
48
14
0
02 Apr 2024
Expandable Subspace Ensemble for Pre-Trained Model-Based
  Class-Incremental Learning
Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning
Da-Wei Zhou
Hai-Long Sun
Han-Jia Ye
De-Chuan Zhan
CLL
81
60
0
18 Mar 2024
BECoTTA: Input-dependent Online Blending of Experts for Continual
  Test-time Adaptation
BECoTTA: Input-dependent Online Blending of Experts for Continual Test-time Adaptation
Daeun Lee
Jaehong Yoon
Sung Ju Hwang
CLLTTA
101
6
0
13 Feb 2024
Continual Learning for Large Language Models: A Survey
Continual Learning for Large Language Models: A Survey
Tongtong Wu
Linhao Luo
Yuan-Fang Li
Shirui Pan
Thuy-Trang Vu
Gholamreza Haffari
CLLLRMKELM
113
122
0
02 Feb 2024
Continual Learning with Pre-Trained Models: A Survey
Continual Learning with Pre-Trained Models: A Survey
Da-Wei Zhou
Hai-Long Sun
Jingyi Ning
Han-Jia Ye
De-Chuan Zhan
CLLKELM
90
76
0
29 Jan 2024
What, How, and When Should Object Detectors Update in Continually
  Changing Test Domains?
What, How, and When Should Object Detectors Update in Continually Changing Test Domains?
Jayeon Yoo
Dongkwan Lee
Inseop Chung
Donghyun Kim
Nojun Kwak
OODVLMTTA
87
5
0
12 Dec 2023
Improving Plasticity in Online Continual Learning via Collaborative
  Learning
Improving Plasticity in Online Continual Learning via Collaborative Learning
Maorong Wang
Nicolas Michel
Ling Xiao
Toshihiko Yamasaki
CLL
70
9
0
01 Dec 2023
One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for
  Continual Learning
One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning
Doyoung Kim
Susik Yoon
Dongmin Park
Youngjun Lee
Hwanjun Song
Jihwan Bang
Jae-Gil Lee
VLM
85
3
0
18 Nov 2023
A Survey on Continual Semantic Segmentation: Theory, Challenge, Method
  and Application
A Survey on Continual Semantic Segmentation: Theory, Challenge, Method and Application
Bo Yuan
Danpei Zhao
3DVCLL
85
11
0
22 Oct 2023
PILOT: A Pre-Trained Model-Based Continual Learning Toolbox
PILOT: A Pre-Trained Model-Based Continual Learning Toolbox
Hai-Long Sun
Da-Wei Zhou
Han-Jia Ye
De-Chuan Zhan
CLL
186
34
0
13 Sep 2023
Rethinking Momentum Knowledge Distillation in Online Continual Learning
Rethinking Momentum Knowledge Distillation in Online Continual Learning
Nicolas Michel
Maorong Wang
L. Xiao
T. Yamasaki
CLL
75
9
0
06 Sep 2023
RanPAC: Random Projections and Pre-trained Models for Continual Learning
RanPAC: Random Projections and Pre-trained Models for Continual Learning
Mark D Mcdonnell
Dong Gong
Amin Parvaneh
Ehsan Abbasnejad
Anton Van Den Hengel
VLMCLL
84
108
0
05 Jul 2023
Regularizing with Pseudo-Negatives for Continual Self-Supervised
  Learning
Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning
Sungmin Cha
Kyunghyun Cho
Taesup Moon
BDLCLL
67
3
0
08 Jun 2023
AdaCL:Adaptive Continual Learning
AdaCL:Adaptive Continual Learning
Elif Ceren Gok
Murat Onur Yildirim
Mert Kilickaya
Joaquin Vanschoren
CLL
76
1
0
23 Mar 2023
Computationally Budgeted Continual Learning: What Does Matter?
Computationally Budgeted Continual Learning: What Does Matter?
Ameya Prabhu
Hasan Hammoud
P. Dokania
Philip Torr
Ser-Nam Lim
Guohao Li
Adel Bibi
CLL
68
63
0
20 Mar 2023
Is forgetting less a good inductive bias for forward transfer?
Is forgetting less a good inductive bias for forward transfer?
Jiefeng Chen
Timothy Nguyen
Dilan Görür
Arslan Chaudhry
CLL
92
14
0
14 Mar 2023
Revisiting Class-Incremental Learning with Pre-Trained Models:
  Generalizability and Adaptivity are All You Need
Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need
Da-Wei Zhou
Han-Jia Ye
De-Chuan Zhan
Ziwei Liu
CLL
86
110
0
13 Mar 2023
Continual Pre-training of Language Models
Continual Pre-training of Language Models
Zixuan Ke
Yijia Shao
Haowei Lin
Tatsuya Konishi
Gyuhak Kim
Bin Liu
CLLKELM
88
138
0
07 Feb 2023
A Comprehensive Survey of Continual Learning: Theory, Method and
  Application
A Comprehensive Survey of Continual Learning: Theory, Method and Application
Liyuan Wang
Xingxing Zhang
Hang Su
Jun Zhu
KELMCLL
170
693
0
31 Jan 2023
Online Hyperparameter Optimization for Class-Incremental Learning
Online Hyperparameter Optimization for Class-Incremental Learning
Yaoyao Liu
Yingying Li
Bernt Schiele
Qianru Sun
CLL
68
33
0
11 Jan 2023
CODA-Prompt: COntinual Decomposed Attention-based Prompting for
  Rehearsal-Free Continual Learning
CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual Learning
James Smith
Leonid Karlinsky
V. Gutta
Paola Cascante-Bonilla
Donghyun Kim
Assaf Arbelle
Yikang Shen
Rogerio Feris
Z. Kira
CLLVPVLMVLM
93
295
0
23 Nov 2022
NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision
  Research
NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research
J. Bornschein
Alexandre Galashov
Ross Hemsley
Amal Rannen-Triki
Yutian Chen
...
Angeliki Lazaridou
Yee Whye Teh
Andrei A. Rusu
Razvan Pascanu
MarcÁurelio Ranzato
OODVLMAI4TS
90
18
0
15 Nov 2022
A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental
  Learning
A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning
Da-Wei Zhou
Qiwen Wang
Han-Jia Ye
De-Chuan Zhan
76
136
0
26 May 2022
DualPrompt: Complementary Prompting for Rehearsal-free Continual
  Learning
DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning
Zifeng Wang
Zizhao Zhang
Sayna Ebrahimi
Ruoxi Sun
Han Zhang
...
Xiaoqi Ren
Guolong Su
Vincent Perot
Jennifer Dy
Tomas Pfister
CLLVLMVPVLM
117
501
0
10 Apr 2022
FOSTER: Feature Boosting and Compression for Class-Incremental Learning
FOSTER: Feature Boosting and Compression for Class-Incremental Learning
Fu Lee Wang
Da-Wei Zhou
Han-Jia Ye
De-Chuan Zhan
CLL
79
258
0
10 Apr 2022
Continual Test-Time Domain Adaptation
Continual Test-Time Domain Adaptation
Qin Wang
Olga Fink
Luc Van Gool
Dengxin Dai
OODTTA
109
428
0
25 Mar 2022
On Generalizing Beyond Domains in Cross-Domain Continual Learning
On Generalizing Beyond Domains in Cross-Domain Continual Learning
Christian Simon
M. Faraki
Yi-Hsuan Tsai
Xiang Yu
S. Schulter
Yumin Suh
Mehrtash Harandi
Manmohan Chandraker
FedMLOODCLL
60
32
0
08 Mar 2022
Rebalancing Batch Normalization for Exemplar-based Class-Incremental
  Learning
Rebalancing Batch Normalization for Exemplar-based Class-Incremental Learning
Sungmin Cha
Sungjun Cho
Dasol Hwang
Sunwon Hong
Moontae Lee
Taesup Moon
CLL
106
19
0
29 Jan 2022
Class-Incremental Continual Learning into the eXtended DER-verse
Class-Incremental Continual Learning into the eXtended DER-verse
Matteo Boschini
Lorenzo Bonicelli
Pietro Buzzega
Angelo Porrello
Simone Calderara
CLLBDL
90
140
0
03 Jan 2022
PyCIL: A Python Toolbox for Class-Incremental Learning
PyCIL: A Python Toolbox for Class-Incremental Learning
Da-Wei Zhou
Fu Lee Wang
Han-Jia Ye
De-Chuan Zhan
CLL
95
98
0
23 Dec 2021
Learning to Prompt for Continual Learning
Learning to Prompt for Continual Learning
Zifeng Wang
Zizhao Zhang
Chen-Yu Lee
Han Zhang
Ruoxi Sun
Xiaoqi Ren
Guolong Su
Vincent Perot
Jennifer Dy
Tomas Pfister
CLLVPVLMKELMVLM
101
785
0
16 Dec 2021
Self-Supervised Models are Continual Learners
Self-Supervised Models are Continual Learners
Enrico Fini
Victor G. Turrisi da Costa
Xavier Alameda-Pineda
Elisa Ricci
Alahari Karteek
Julien Mairal
BDLCLLSSL
86
166
0
08 Dec 2021
CLEVA-Compass: A Continual Learning EValuation Assessment Compass to
  Promote Research Transparency and Comparability
CLEVA-Compass: A Continual Learning EValuation Assessment Compass to Promote Research Transparency and Comparability
Martin Mundt
Steven Braun
Quentin Delfosse
Kristian Kersting
73
35
0
07 Oct 2021
Efficiently Identifying Task Groupings for Multi-Task Learning
Efficiently Identifying Task Groupings for Multi-Task Learning
Christopher Fifty
Ehsan Amid
Zhe Zhao
Tianhe Yu
Rohan Anil
Chelsea Finn
287
254
1
10 Sep 2021
SSUL: Semantic Segmentation with Unknown Label for Exemplar-based
  Class-Incremental Learning
SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning
Sungmin Cha
Beomyoung Kim
Y. Yoo
Taesup Moon
CLL
65
91
0
22 Jun 2021
DER: Dynamically Expandable Representation for Class Incremental
  Learning
DER: Dynamically Expandable Representation for Class Incremental Learning
Shipeng Yan
Jiangwei Xie
Xuming He
CLL
67
454
0
31 Mar 2021
Class-incremental learning: survey and performance evaluation on image
  classification
Class-incremental learning: survey and performance evaluation on image classification
Marc Masana
Xialei Liu
Bartlomiej Twardowski
Mikel Menta
Andrew D. Bagdanov
Joost van de Weijer
CLL
79
692
0
28 Oct 2020
An Image is Worth 16x16 Words: Transformers for Image Recognition at
  Scale
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy
Lucas Beyer
Alexander Kolesnikov
Dirk Weissenborn
Xiaohua Zhai
...
Matthias Minderer
G. Heigold
Sylvain Gelly
Jakob Uszkoreit
N. Houlsby
ViT
667
41,369
0
22 Oct 2020
The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution
  Generalization
The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization
Dan Hendrycks
Steven Basart
Norman Mu
Saurav Kadavath
Frank Wang
...
Samyak Parajuli
Mike Guo
Basel Alomair
Jacob Steinhardt
Justin Gilmer
OOD
347
1,751
0
29 Jun 2020
CPR: Classifier-Projection Regularization for Continual Learning
CPR: Classifier-Projection Regularization for Continual Learning
Sungmin Cha
Hsiang Hsu
Taebaek Hwang
Flavio du Pin Calmon
Taesup Moon
CLL
68
77
0
12 Jun 2020
Modeling the Background for Incremental Learning in Semantic
  Segmentation
Modeling the Background for Incremental Learning in Semantic Segmentation
Fabio Cermelli
Massimiliano Mancini
Samuel Rota Buló
Elisa Ricci
Barbara Caputo
CLLVLM
48
284
0
03 Feb 2020
Maintaining Discrimination and Fairness in Class Incremental Learning
Maintaining Discrimination and Fairness in Class Incremental Learning
Bowen Zhao
Xi Xiao
Guojun Gan
Bin Zhang
Shutao Xia
CLL
130
430
0
16 Nov 2019
Natural Adversarial Examples
Natural Adversarial Examples
Dan Hendrycks
Kevin Zhao
Steven Basart
Jacob Steinhardt
Basel Alomair
OODD
212
1,482
0
16 Jul 2019
Large Scale Incremental Learning
Large Scale Incremental Learning
Yue Wu
Yinpeng Chen
Lijuan Wang
Yuancheng Ye
Zicheng Liu
Yandong Guo
Y. Fu
CLL
102
1,258
0
30 May 2019
Which Tasks Should Be Learned Together in Multi-task Learning?
Which Tasks Should Be Learned Together in Multi-task Learning?
Trevor Scott Standley
Amir Zamir
Dawn Chen
Leonidas Guibas
Jitendra Malik
Silvio Savarese
103
517
0
18 May 2019
Three scenarios for continual learning
Three scenarios for continual learning
Gido M. van de Ven
A. Tolias
CLL
99
895
0
15 Apr 2019
Efficient Lifelong Learning with A-GEM
Efficient Lifelong Learning with A-GEM
Arslan Chaudhry
MarcÁurelio Ranzato
Marcus Rohrbach
Mohamed Elhoseiny
CLL
210
1,458
0
02 Dec 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
125
889
0
16 May 2018
Taskonomy: Disentangling Task Transfer Learning
Taskonomy: Disentangling Task Transfer Learning
Amir Zamir
Alexander Sax
Bokui (William) Shen
Leonidas Guibas
Jitendra Malik
Silvio Savarese
126
1,221
0
23 Apr 2018
Continual Lifelong Learning with Neural Networks: A Review
Continual Lifelong Learning with Neural Networks: A Review
G. I. Parisi
Ronald Kemker
Jose L. Part
Christopher Kanan
S. Wermter
KELMCLL
193
2,895
0
21 Feb 2018
12
Next