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2001.05755
Cited By
ScaIL: Classifier Weights Scaling for Class Incremental Learning
IEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2020
16 January 2020
Eden Belouadah
Adrian Daniel Popescu
CLL
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Papers citing
"ScaIL: Classifier Weights Scaling for Class Incremental Learning"
50 / 53 papers shown
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Zhuo Xu
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Yifan Liang
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Qingfang Zheng
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Decomposed Distribution Matching in Dataset Condensation
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Mohammad Saeed Ebrahimi Saadabadi
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Task Confusion and Catastrophic Forgetting in Class-Incremental Learning: A Mathematical Framework for Discriminative and Generative Modelings
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316
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Foundation Model-Powered 3D Few-Shot Class Incremental Learning via Training-free Adaptor
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Sahar Ahmadi
A. Cheraghian
Morteza Saberi
Md. Towsif Abir
Hamidreza Dastmalchi
Farookh Hussain
Shafin Rahman
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318
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ATOM: Attention Mixer for Efficient Dataset Distillation
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A. Sajedi
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Lucy Z. Liu
Y. Lawryshyn
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481
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Catastrophic Forgetting in Deep Learning: A Comprehensive Taxonomy
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332
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Not All Data Matters: An End-to-End Adaptive Dataset Pruning Framework for Enhancing Model Performance and Efficiency
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Hongchao Yang
Suhan Guo
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220
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DataDAM: Efficient Dataset Distillation with Attention Matching
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Samir Khaki
Ehsan Amjadian
Lucy Z. Liu
Y. Lawryshyn
Konstantinos N. Plataniotis
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104
0
29 Sep 2023
S3C: Self-Supervised Stochastic Classifiers for Few-Shot Class-Incremental Learning
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Soma Biswas
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253
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Bayesian Pseudo-Coresets via Contrastive Divergence
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340
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A Comprehensive Survey of Continual Learning: Theory, Method and Application
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Xingxing Zhang
Hang Su
Jun Zhu
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Cold Start Streaming Learning for Deep Networks
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Anastasios Kyrillidis
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243
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Dataset Distillation via Factorization
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Kai Wang
Xingyi Yang
Jingwen Ye
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449
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Efficient Dataset Distillation Using Random Feature Approximation
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Noel Loo
Ramin Hasani
Alexander Amini
Daniela Rus
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293
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Attribution-aware Weight Transfer: A Warm-Start Initialization for Class-Incremental Semantic Segmentation
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René Schuster
Joost van de Weijer
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304
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Delving into Effective Gradient Matching for Dataset Condensation
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Jiaqi Gu
Mingjie Liu
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Progressive Voronoi Diagram Subdivision: Towards A Holistic Geometric Framework for Exemplar-free Class-Incremental Learning
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334
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DC-BENCH: Dataset Condensation Benchmark
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Ruochen Wang
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476
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Graph Condensation via Receptive Field Distribution Matching
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Shanchuan Li
Xinshi Chen
Le Song
DD
264
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28 Jun 2022
Queried Unlabeled Data Improves and Robustifies Class-Incremental Learning
Tianlong Chen
Sijia Liu
Shiyu Chang
Lisa Amini
Zinan Lin
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302
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15 Jun 2022
Few-shot Class-incremental Learning for 3D Point Cloud Objects
European Conference on Computer Vision (ECCV), 2022
T. Chowdhury
A. Cheraghian
Sameera Ramasinghe
Sahar Ahmadi
Morteza Saberi
Shafin Rahman
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244
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Dataset Pruning: Reducing Training Data by Examining Generalization Influence
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Shuo Yang
Zeke Xie
Hanyu Peng
Minjing Xu
Mingming Sun
P. Li
DD
636
163
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19 May 2022
CAFE: Learning to Condense Dataset by Aligning Features
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Bo Zhao
Xiangyu Peng
Zheng Zhu
Shuo Yang
Shuo Wang
Guan Huang
Hakan Bilen
Xinchao Wang
Yang You
DD
385
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03 Mar 2022
Self-Paced Imbalance Rectification for Class Incremental Learning
Zhiheng Liu
Kai Zhu
Yang Cao
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247
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Improving Vision Transformers for Incremental Learning
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Yinpeng Chen
Ying Jin
Zicheng Liu
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Coarse-To-Fine Incremental Few-Shot Learning
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Yuwen Tan
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299
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Dataset Condensation with Distribution Matching
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Hakan Bilen
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Recent Advances of Continual Learning in Computer Vision: An Overview
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Haoxuan Qu
Hossein Rahmani
Kepeng Xu
Bryan M. Williams
Jun Liu
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625
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Generalized and Incremental Few-Shot Learning by Explicit Learning and Calibration without Forgetting
Anna Kukleva
Hilde Kuehne
Bernt Schiele
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256
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0
18 Aug 2021
A First Look at Class Incremental Learning in Deep Learning Mobile Traffic Classification
Traffic Monitoring and Analysis (TMA), 2021
Giampaolo Bovenzi
Lixuan Yang
A. Finamore
Giuseppe Aceto
D. Ciuonzo
A. Pescapé
Dario Rossi
218
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09 Jul 2021
Tackling Catastrophic Forgetting and Background Shift in Continual Semantic Segmentation
Arthur Douillard
Yifu Chen
Arnaud Dapogny
Matthieu Cord
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229
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Generative Feature-driven Image Replay for Continual Learning
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Kevin Thandiackal
Tiziano Portenier
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M. Gabrani
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Energy Aligning for Biased Models
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Chen Chen
Qi Ju
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135
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Class-Incremental Learning with Generative Classifiers
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Replay in Deep Learning: Current Approaches and Missing Biological Elements
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G. Krishnan
M. Bazhenov
H. Siegelmann
T. Sejnowski
Christopher Kanan
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328
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ClaRe: Practical Class Incremental Learning By Remembering Previous Class Representations
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125
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Dataset Condensation with Differentiable Siamese Augmentation
International Conference on Machine Learning (ICML), 2021
Bo Zhao
Hakan Bilen
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Self-Supervised Features Improve Open-World Learning
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Do Not Forget to Attend to Uncertainty while Mitigating Catastrophic Forgetting
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Online Continual Learning in Image Classification: An Empirical Survey
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Incremental Learning from Low-labelled Stream Data in Open-Set Video Face Recognition
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A Review of Open-World Learning and Steps Toward Open-World Learning Without Labels
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PLOP: Learning without Forgetting for Continual Semantic Segmentation
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Arnaud Dapogny
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435
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0
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A Comprehensive Study of Class Incremental Learning Algorithms for Visual Tasks
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Ioannis Kanellos
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Active Class Incremental Learning for Imbalanced Datasets
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Memory Efficient Class-Incremental Learning for Image Classification
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Haibo Wang
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