iCaRL: Incremental Classifier and Representation Learning

Cited by (1,014)

Items 601–700 of 1,014

1. Class-Incremental Semantic Segmentation of Aerial Images via Pixel-Level Feature Generation and Task-Wise Distillation
   Lianlei Shan, Weiqiang Wang, Ke Lv, Bin Luo · 2022 · IEEE Transactions on Geoscience and Remote Sensing
2. Balancing Stability and Plasticity Through Advanced Null Space in Continual Learning
   Yajing Kong, Liu Liu, Zhen Wang, Dacheng Tao · 2022 · Lecture notes in computer science
3. ILETC: Incremental learning for encrypted traffic classification using generative replay and exemplar
   Wenbin Zhu, Xiuli Ma, Yanliang Jin, Rui Wang · 2023 · Computer Networks
4. Improved Continually Evolved Classifiers for Few-Shot Class-Incremental Learning
   Ye Wang, Guoshuai Zhao, Xueming Qian · 2023 · IEEE Transactions on Circuits and Systems for Video Technology
5. Few-Shot Class-Incremental SAR Target Recognition via Cosine Prototype Learning
   Yan Chun Zhao, Lingjun Zhao, Ding Ding, Dewen Hu, Gangyao Kuang, Li Liu · 2023 · IEEE Transactions on Geoscience and Remote Sensing
6. Efficient Spiking Neural Networks with Sparse Selective Activation for Continual Learning
   Jiangrong Shen, Wenyao Ni, Qi Xu, Huajin Tang · 2024 · Proceedings of the AAAI Conference on Artificial Intelligence
7. Delving Into Multi-Modal Multi-Task Foundation Models for Road Scene Understanding: From Learning Paradigm Perspectives
   Sheng Xu Luo, Wei Chen, Wanxin Tian, Rui Liu, Luanxuan Hou, Xiubao Zhang, Haifeng Shen, Ruiqi Wu, Shuyi Geng, Yi Zhou et al. · 2024 · IEEE Transactions on Intelligent Vehicles
8. A relationship-aware calibrated prototypical network for fault incremental diagnosis of electric motors without reserved samples
   Ke Yue, Jipu Li, Shuhan Deng, Chee Keong Kwoh, Zhuyun Chen, Weihua Li · 2024 · Reliability Engineering & System Safety
9. Class Incremental Learning with Multi-Teacher Distillation
   Haitao Wen, Lili Pan, Yu Dai, Heqian Qiu, Lanxiao Wang, Qingbo Wu, Hongliang Li · 2024 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
10. Resurrecting Old Classes with New Data for Exemplar-Free Continual Learning
    Dipam Goswami, Albin Soutif--Cormerais, Yuyang Liu, Sandesh Kamath, Bartłomiej Twardowski, Joost van de Weijer · 2024 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
11. Generalized Class Incremental Learning
    Fei Mi, Lingjing Kong, Tao Lin, Kaicheng Yu, Boi V. Faltings · 2020 · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
12. Adaptive Progressive Continual Learning
    Ju Xu, Jin Ma, Xuesong Gao, Zhanxing Zhu · 2021 · IEEE Transactions on Pattern Analysis and Machine Intelligence
13. Continual Domain Incremental Learning for Chest X-Ray Classification in Low-Resource Clinical Settings
    Shikhar Srivastava, Mohammad K. Yaqub, Karthik Nandakumar, Zongyuan Ge, Dwarikanath Mahapatra · 2021 · Lecture notes in computer science
14. ELLE: Efficient Lifelong Pre-training for Emerging Data
    Yujia Qin, Jiajie Zhang, Yankai Lin, Zhiyuan Liu, Peng Li, Maosong Sun, Jie Zhou · 2022 · Findings of the Association for Computational Linguistics: ACL (Findings of ACL)
15. RBC: Rectifying the Biased Context in Continual Semantic Segmentation
    Hanbin Zhao, Fengyu Yang, Xinghe Fu, Xi Li · 2022 · Lecture notes in computer science
16. Historical Information-Guided Class-Incremental Semantic Segmentation in Remote Sensing Images
    Xuee Rong, Xian Sun, Wenhui Diao, Peijin Wang, Zhiqiang Yuan, Hongqi Wang · 2022 · IEEE Transactions on Geoscience and Remote Sensing
17. Adaptive Orthogonal Projection for Batch and Online Continual Learning
    Yiduo Guo, Wenpeng Hu, Dongyan Zhao, Bing Liu · 2022 · Proceedings of the AAAI Conference on Artificial Intelligence
18. Learn and Review: Enhancing Continual Named Entity Recognition via Reviewing Synthetic Samples
    Yu Xia, Quan Wang, Yajuan Lyu, Zhu Yong, Wenhao Wu, Sujian Li, Dai Dai · 2022 · Findings of the Association for Computational Linguistics: ACL (Findings of ACL)
19. Open Long-Tailed Recognition in a Dynamic World
    Ziwei Liu, Zhongqi Miao, Xiaohang Zhan, Jiayun Wang, Boqing Gong, Stella X. Yu · 2022 · IEEE Transactions on Pattern Analysis and Machine Intelligence
20. Open set maize seed variety classification using hyperspectral imaging coupled with a dual deep SVDD-based incremental learning framework
    Liu Zhang, Jinze Huang, Yaoguang Wei, Jincun Liu, Dong Un An, Jianwei Wu · 2023 · Expert Systems with Applications
21. Online Continual Learning on Class Incremental Blurry Task Configuration with Anytime Inference
    Hyunseo Koh, Dahyun Kim, Jung-Woo Ha, Jonghyun Choi · 2021 · arXiv (Cornell University)
22. Inherit With Distillation and Evolve With Contrast: Exploring Class Incremental Semantic Segmentation Without Exemplar Memory
    Dan-Pei Zhao, Bo Yuan, Zhen-Wei Shi · 2023 · IEEE Transactions on Pattern Analysis and Machine Intelligence
23. Object Detection in Adverse Weather for Autonomous Vehicles Based on Sensor Fusion and Incremental Learning
    Huiping Su, Hongbo Gao, Xinmiao Wang, Xiaozhao Fang, Qingchao Liu, Guang-Bin Huang, Xin Li, Qi Ping Cao · 2024 · IEEE Transactions on Instrumentation and Measurement
24. An Overview of Deep Neural Networks for Few-Shot Learning
    Juan Zhao, Lili Kong, Jiancheng Lv · 2024 · Big Data Mining and Analytics
25. Efficient Multi-Domain Learning by Covariance Normalization
    Yunsheng Li, Nuno M. Vasconcelos · 2019 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
26. Take Goods from Shelves
    Hao Yu, Yanwei Fu, Yu–Gang Jiang · 2019 · International Conference on Multimedia Retrieval
27. Meta-Learning Improves Lifelong Relation Extraction
    Abiola Obamuyide, Andreas Vlachos · 2019 · RepL4NLP@ACL
28. Heterogeneous Few-Shot Model Rectification With Semantic Mapping
    Han-Jia Ye, De‐Chuan Zhan, Yuan Ying Jiang, Zhi‐Hua Zhou · 2020 · IEEE Transactions on Pattern Analysis and Machine Intelligence
29. Contextual Transformation Networks for Online Continual Learning
    Quang Pham, Chenghao Liu, Doyen Sahoo, Steven C. H. Hoi · 2021 · Singapore Management University Institutional Knowledge (InK) (Singapore Management University)
30. TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph Completion
    Jiapeng Wu, Yishi Xu, Yingxue Zhang, Chen Ma, Mark Coates, Jackie Chi Kit Cheung · 2021 · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
31. Hierarchical Memory Learning for Fine-Grained Scene Graph Generation
    Youming Deng, Yansheng Li, Yongjun Zhang, Xiang Xiang, Jian Wang, Jingdong Chen, Jiayi Ma · 2022 · Lecture notes in computer science
32. Sample Condensation in Online Continual Learning
    Mattia Sangermano, Antonio Carta, Andrea Cossu, Davide Bacciu · 2022 · International Joint Conference on Neural Networks (IJCNN)
33. Class-incremental object detection
    Na Dong, Yongqiang Zhang, Mingli Ding, Yancheng Bai · 2023 · Pattern Recognition
34. Self-Paced Weight Consolidation for Continual Learning
    Wei Wei Cong, Yang Cong, Gan Sun, Yuyang Liu, Jiahua Dong · 2023 · IEEE Transactions on Circuits and Systems for Video Technology
35. First Session Adaptation: A Strong Replay-Free Baseline for Class-Incremental Learning
    Aristeidis Panos, Yuriko Kobe, Daniel Olmeda Reino, Rahaf Aljundi, Richard E. Turner · 2023 · IEEE/CVF International Conference on Computer Vision (ICCV)
36. Analogical Learning-Based Few-Shot Class-Incremental Learning
    Jiashuo Li, Songlin Dong, Yihong Gong, Yuhang He, Xing Wei · 2024 · IEEE Transactions on Circuits and Systems for Video Technology
37. A Study on Catastrophic Forgetting in Deep LSTM Networks
    Monika Schak, Alexander Gepperth · 2019 · Lecture notes in computer science
38. Dropout as an Implicit Gating Mechanism For Continual Learning
    Seyed Iman Mirzadeh, Mehrdad Farajtabar, Hassan G Ghasemzadeh · 2020 · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
39. Incremental Concept Learning via Online Generative Memory Recall
    Huaiyu Li, Weiming Dong, Bao-Gang Hu · 2020 · IEEE Transactions on Neural Networks and Learning Systems
40. Continual learning strategies for cancer-independent detection of lymph node metastases
    Péter Bándi, Maschenka C. A. Balkenhol, Marcory van Dijk, Michel Kok, Bram van Ginneken, Jeroen A. W. M. van der Laak, Geert J. S. Litjens · 2023 · Medical Image Analysis
41. CoMFormer: Continual Learning in Semantic and Panoptic Segmentation
    Fabio Cermelli, Matthieu Cord, Arthur Douillard · 2023 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
42. CTP: Towards Vision-Language Continual Pretraining via Compatible Momentum Contrast and Topology Preservation
    Hongguang Zhu, Yunchao Wei, Xiaodan Liang, Chunjie Zhang, Yao Zhao · 2023 · IEEE/CVF International Conference on Computer Vision (ICCV)
43. Bayesian Embeddings for Few-Shot Open World Recognition
    John Willes, James Harrison, Ali Harakeh, Chelsea Finn, Marco Pavone, Steven L. Waslander · 2022 · IEEE Transactions on Pattern Analysis and Machine Intelligence
44. Semantics-Driven Generative Replay for Few-Shot Class Incremental Learning
    Aishwarya Agarwal, Biplab Banerjee, Fabio Cuzzolin A, Subhasis Chaudhuri · 2022 · ACM International Conference on Multimedia (ACM MM)
45. Federated probability memory recall for federated continual learning
    Zhe Wang, Yu Zhang, Xinlei Xu, Zhiling Fu, Hai Yang, Wenli Du · 2023 · Information Sciences
46. Gradient-Semantic Compensation for Incremental Semantic Segmentation
    Wei Wei Cong, Yang Cong, Jiahua Dong, Gan Sun, Henghui Ding · 2023 · IEEE Transactions on Multimedia
47. Pseudo-set Frequency Refinement architecture for fine-grained few-shot class-incremental learning
    Zicheng Pan, Weichuan Zhang, Xiaohan Yu, Miaohua Zhang, Yongsheng Gao · 2024 · Pattern Recognition
48. Reserving embedding space for new fault types: A new continual learning method for bearing fault diagnosis
    Hongyan Zhu, Changqing Shen, Lin Li, Dong Wang, Weiguo Huang, Zhongkui Zhu · 2024 · Reliability Engineering & System Safety
49. iKAN: Global Incremental Learning with KAN for Human Activity Recognition Across Heterogeneous Datasets
    Mengxi Liu, Sizhen Bian, Bo Zhou, Paul Lukowicz · 2024 · ACM International Symposium on Wearable Computers (ISWC)
50. A Survey on WiFi-based Human Identification: Scenarios, Challenges, and Current Solutions
    Zhongcheng Wei, Wei Chen, Shuli Ning, Weidong Lin, Nan Li, Bin Lian, Xiang Sun, Jijun Zhao · 2024 · ACM Transactions on Sensor Networks
51. Dynamic branch layer fusion: A new continual learning method for rotating machinery fault diagnosis
    Changqing Shen, Zhenzhong He, Bojian Chen, Weiguo Huang, Lin Li, Dong Wang · 2025 · Knowledge-Based Systems
52. Re-Fed+: A Better Replay Strategy for Federated Incremental Learning
    Yichen Li, Haozhao Wang, Yining Qi, Wei Liu, Ruixuan Li · 2025 · IEEE Transactions on Pattern Analysis and Machine Intelligence
53. Marginal Replay vs Conditional Replay for Continual Learning
    Timothée Lesort, Alexander Gepperth, Andrei Stoian, David Filliat · 2019 · Lecture notes in computer science
54. Bi-Objective Continual Learning: Learning ‘New’ While Consolidating ‘Known’
    Xiaoyu Tao, Xiaopeng Hong, Xinyuan Chang, Yihong Gong · 2020 · Proceedings of the AAAI Conference on Artificial Intelligence
55. Unsupervised Model Personalization While Preserving Privacy and Scalability: An Open Problem
    Matthias De Lange, Xu Jia, Sarah Parisot, Aleš Leonardis, Greg Slabaugh, Tinne Tuytelaars · 2020 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
56. Tell me what this is: Few-Shot Incremental Object Learning by a Robot
    Ali Ayub, Alan R. Wagner · 2020 · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
57. Continual Learning of New Diseases with Dual Distillation and Ensemble Strategy
    Zhuoyun Li, Changhong Zhong, Ruixuan Wang, Wei‐Shi Zheng · 2020 · Lecture notes in computer science
58. Do not Forget to Attend to Uncertainty while Mitigating Catastrophic Forgetting
    Vinod K Kurmi, Badri N. Patro, Venkatesh K. Subramanian, Vinay P. Namboodiri · 2021 · IEEE Winter Conference on Applications of Computer Vision
59. Continual Learning for Image-Based Camera Localization
    Shuzhe Wang, Zakaria Laskar, Iaroslav Melekhov, Xiaotian Li, Juho Kannala · 2021 · IEEE/CVF International Conference on Computer Vision (ICCV)
60. Continuous Learning Method of Radar HRRP Based on CVAE-GAN
    Xungen Li, Wenqing Ouyang, Mian Pan, Shuaishuai Lv, Qi Ma · 2023 · IEEE Transactions on Geoscience and Remote Sensing
61. Geometry and Uncertainty-Aware 3D Point Cloud Class-Incremental Semantic Segmentation
    Yuwei Yang, Munawar Hayat, Zhao Jin, Chao Ren, Yin-Jie Lei · 2023 · Computer Vision and Pattern Recognition
62. Continual Segment: Towards a Single, Unified and Non-forgetting Continual Segmentation Model of 143 Whole-body Organs in CT Scans
    Zhanghexuan Ji, Dazhou Guo, Puyang Wang, Ke Yan, Le Lü, Minfeng Xu, Qifeng Wang, Jia Ge, Mingchen Gao, Xianghua Ye et al. · 2023 · IEEE/CVF International Conference on Computer Vision (ICCV)
63. Regularization Shortcomings for Continual Learning
    Timothée Lesort, Andrei Stoian, Filliat, David · 2019 · arXiv (Cornell University)
64. Optimizing Reusable Knowledge for Continual Learning via Metalearning
    Julio Hurtado, Alain Raymond-Sáez, Álvaro Soto · 2021 · arXiv (Cornell University)
65. Adversarial Feature Alignment: Avoid Catastrophic Forgetting in Incremental Task Lifelong Learning
    Yao, Xin, Huang, Tianchi, Wu, Chenglei, Zhang, Rui-Xiao, Sun, Lifeng · 2019 · Neural Computation
66. Collaborative and Incremental Learning for Modulation Classification With Heterogeneous Local Dataset in Cognitive IoT
    Peihan Qi, Xiaoyu Zhou, Yuanlei Ding, Shilian Zheng, Tao Jiang, Zan Li · 2022 · IEEE Transactions on Green Communications and Networking
67. Sparsified Subgraph Memory for Continual Graph Representation Learning
    Xikun Zhang, Dongjin Song, Dacheng Tao · 2022 · Proceedings
68. Do Pre-trained Models Benefit Equally in Continual Learning?
    Kuan-Ying Lee, Yuanyi Zhong, Yu-Xiong Wang · 2023 · IEEE Winter Conference on Applications of Computer Vision
69. SSFE-Net: Self-Supervised Feature Enhancement for Ultra-Fine-Grained Few-Shot Class Incremental Learning
    Pan, Zicheng, Yu, Xiaohan, Zhang, Miaohua, Gao, Yongsheng · 2023 · 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
70. Neural Network-Based Game Theory for Scalable Offloading in Vehicular Edge Computing: A Transfer Learning Approach
    Juan Zhang, Yulei Wu, Geyong Min, Keqin Li · 2024 · IEEE Transactions on Intelligent Transportation Systems
71. Steering Prototypes with Prompt-tuning for Rehearsal-free Continual Learning
    Zhuowei Li, Long Zhao, Zizhao Zhang, Han Zhang, Di Liu, Ting Liu, Dimitris Metaxas · 2024 · IEEE Winter Conference on Applications of Computer Vision
72. Overcoming Catastrophic Forgetting for Multi-Label Class-Incremental Learning
    Xiang Rong Song, Kuang Shu, Songlin Dong, Jie Cheng, Xing Wei, Yihong Gong · 2024 · IEEE Winter Conference on Applications of Computer Vision
73. Imbalanced class incremental learning system: A task incremental diagnosis method for imbalanced industrial streaming data
    Mingkuan Shi, Chuancang Ding, Changqing Shen, Weiguo Huang, Zhongkui Zhu · 2024 · Advanced Engineering Informatics
74. Towards machinery incremental fault diagnosis based on inverted transformer lifelong learning with learnable pruning mechanism
    Haihong Tang, Jiawei Li, Wu-wei Feng, Peng Chen, Hong-tao Xue · 2025 · Engineering Applications of Artificial Intelligence
75. Into the Unknown: Active Monitoring of Neural Networks
    Anna Lukina, Christian Schilling, Thomas A. Henzinger · 2021 · Lecture notes in computer science
76. Ternary Feature Masks: zero-forgetting for task-incremental learning
    Marc Masana, Tinne Tuytelaars, Joost van de Weijer · 2021 · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
77. Tensor feature hallucination for few-shot learning
    Michalis Lazarou, Tania Stathaki, Yannis Avrithis · 2022 · IEEE Winter Conference on Applications of Computer Vision
78. Lifelong Pretraining: Continually Adapting Language Models to Emerging Corpora
    Xisen Jin, Dejiao Zhang, Henghui Zhu, Wei Xiao, Shang-Wen Daniel Li, Xiaokai Wei, Andrew Arnold, Xiang Ren · 2022 · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT)
79. Doodle It Yourself: Class Incremental Learning by Drawing a Few Sketches
    Ayan Kumar Bhunia, Viswanatha Reddy Gajjala, Subhadeep Koley, Rohit Kundu, Aneeshan Sain, Tao Xiang, Yi-Zhe Song · 2022 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
80. Generative negative replay for continual learning
    Gabriele Graffieti, Davide Maltoni, Lorenzo Pellegrini, Vincenzo Lomonaco · 2023 · Neural Networks
81. Rehearsal-free Continual Language Learning via Efficient Parameter Isolation
    Zhicheng Wang, Yufang Liu, Tao Ji, Xiaoling Wang, Yuanbin Wu, Congcong Jiang, Chao Ye, Zhencong Han, Ling Wang, Xu Shao et al. · 2023 · Proceedings of the conference - Association for Computational Linguistics. Meeting
82. ConSlide: Asynchronous Hierarchical Interaction Transformer with Breakup-Reorganize Rehearsal for Continual Whole Slide Image Analysis
    Yanyan Huang, Weiqin Zhao, Shujun Wang, Yu Fu, Yuming Jiang, Lequan Yu · 2023 · IEEE/CVF International Conference on Computer Vision (ICCV)
83. Online Class Incremental Learning on Stochastic Blurry Task Boundary via Mask and Visual Prompt Tuning
    Jun-Yeong Moon, Keon-Hee Park, Jung Uk Kim, Gyeong-Moon Park · 2023 · IEEE/CVF International Conference on Computer Vision (ICCV)
84. Deep Reinforcement Learning amidst Lifelong Non-Stationarity
    Annie Xie, Harrison, James, Chelsea Finn · 2020 · arXiv (Cornell University)
85. Self-Supervised Training Enhances Online Continual Learning
    Jhair Gallardo, Tyler L. Hayes, Christopher Kanan · 2021 · arXiv (Cornell University)
86. CarM
    Soobee Lee, Minindu Weerakoon, Jonghyun Choi, Minjia Zhang, Di Wang, Myeongjae Jeon · 2022 · ACM/IEEE Design Automation Conference (DAC)
87. Class-Incremental Learning for Multi-Label Audio Classification
    Manjunath Mulimani, Annamaria Mesaros · 2024 · IEEE International Conference on Acoustics Speech and Signal Processing
88. SR-FDIL: Synergistic Replay for Federated Domain-Incremental Learning
    Yichen Li, Wenchao Xu, Yining Qi, Haozhao Wang, Ruixuan Li, Song Guo · 2024 · IEEE Transactions on Parallel and Distributed Systems
89. PASS-Net: A Pseudo Classes and Stochastic Classifiers-Based Network for Few-Shot Class-Incremental Automatic Modulation Classification
    Haoyue Tan, Zhenxi Zhang, Yu Li, Xiaoran Shi, Li Wang, Xinyao Yang, Feng Zhou · 2024 · IEEE Transactions on Wireless Communications
90. Convolutional Prompting meets Language Models for Continual Learning
    Anurag Roy, Riddhiman Moulick, Vinay Kumar Verma, Saptarshi Ghosh, Abir Das · 2024 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
91. A Novel Domain Incremental Learning Method for Bearing Fault Diagnosis Based on F&K
    Meidi Sun, Xinmiao Xiao, Tangyan Chen, Qing He, Zhuo Long, Ling Li · 2024 · IEEE Transactions on Industrial Informatics
92. Class-Incremental Learning with CLIP: Adaptive Representation Adjustment and Parameter Fusion
    Linlan Huang, Xusheng Cao, Haori Lu, Xialei Liu · 2024 · Lecture notes in computer science
93. Hybrid neural networks for continual learning inspired by corticohippocampal circuits
    Qianqian Shi, Faqiang Liu, Hongyi Li, Guangyu Li, Luping Shi, Rong Juan Zhao · 2025 · Nature Communications
94. Semi-supervised feature contrast incremental learning framework for bearing fault diagnosis with limited labeled samples
    Xuyang Tao, Changqing Shen, Lin Li, Dong Wang, Juanjuan Shi, Zhongkui Zhu · 2025 · Applied Soft Computing
95. Brain inspired lifelong learning model based on neural based learning classifier system for underwater data classification
    Muhammad Irfan, Zheng Jiangbin, Muhammad Iqbal, Zafar Masood, Muhammad Hassan Arif, Syed Rauf ul Hassan · 2021 · Expert Systems with Applications
96. Learning an Adaptive Meta Model-Generator for Incrementally Updating Recommender Systems
    Danni Peng, Sinno Jialin Pan, Jie Zhang, Anxiang Zeng · 2021 · ACM Conference on Recommender Systems (RecSys)
97. Graph Structure Aware Contrastive Knowledge Distillation for Incremental Learning in Recommender Systems
    Yuening Wang, Yingxue Zhang, Mark Coates · 2021 · ACM International Conference on Information and Knowledge Management (CIKM)
98. Lifelong Event Detection with Knowledge Transfer
    Pengfei Yu, Heng Ji, Prem Natarajan · 2021 · Conference on Empirical Methods in Natural Language Processing (EMNLP)
99. Residual Tuning: Toward Novel Category Discovery Without Labels
    Yu Liu, Tinne Tuytelaars · 2022 · IEEE Transactions on Neural Networks and Learning Systems
100. Multi-Granularity Regularized Re-Balancing for Class Incremental Learning
     Huitong Chen, Yu Wang, Qinghua Hu · 2022 · IEEE Transactions on Knowledge and Data Engineering