MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models | Paper Citation Record

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This paper cites In: Proceedings of the 26th International Con- ference on World Wide Web, pp.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Proceedings of the 26th International Con- ference on World Wide Web, pp

Reference 1

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This paper cites In: Proceedings of the 1st Workshop on Deep Learning for Recommender Systems, pp.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Proceedings of the 1st Workshop on Deep Learning for Recommender Systems, pp

Reference 2

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This paper cites In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowl- edge Discovery and Data Mining, pp.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowl- edge Discovery and Data Mining, pp

Reference 3

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This paper cites In: Proceedings of the 40th International ACM 14 SIGIR Conference on Research and Develop- ment in Information Retrieval, pp.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Proceedings of the 40th International ACM 14 SIGIR Conference on Research and Develop- ment in Information Retrieval, pp

Reference 4

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This paper cites DeepFM: A Factorization-Machine based Neural Network for CTR Prediction.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models DeepFM: A Factorization-Machine based Neural Network for CTR Prediction

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This paper cites xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems

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This paper cites Deep Learning Recommendation Model for Personalization and Recommendation Systems.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Deep Learning Recommendation Model for Personalization and Recommendation Systems

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This paper cites In: International Symposium on Ubiquitious Computing Systems, pp.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: International Symposium on Ubiquitious Computing Systems, pp

Reference 9

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This paper cites In: Proceedings of the 15th Inter- national Conference on Intelligent User Inter- faces, pp.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Proceedings of the 15th Inter- national Conference on Intelligent User Inter- faces, pp

Reference 10

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This paper cites In: Proceedings of the 29th ACM International Conference on Information & Knowledge Management, pp.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Proceedings of the 29th ACM International Conference on Information & Knowledge Management, pp

Reference 11

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This paper cites In: 2023 5th Interna- tional Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI), pp.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: 2023 5th Interna- tional Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI), pp

Reference 12

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This paper cites In: Proceedings of the 2nd ACM Conference on Electronic Commerce, pp.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Proceedings of the 2nd ACM Conference on Electronic Commerce, pp

Reference 13

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This paper cites In: Proceedings of the 14th ACM Conference on Recommender Systems.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Proceedings of the 14th ACM Conference on Recommender Systems

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This paper cites In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval

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This paper cites In: Proceedings of the ACM Web Conference.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Proceedings of the ACM Web Conference

Reference 16

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This paper cites 2861–2868 (2020).

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models 2861–2868 (2020)

Reference 17

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This paper cites In: Proceedings of the European Conference on Computer Vision 15 (ECCV) (2018).

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Proceedings of the European Conference on Computer Vision 15 (ECCV) (2018)

Reference 18

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This paper cites Three scenarios for continual learning.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Three scenarios for continual learning

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This paper cites A Comprehensive Study of Class Incremental Learning Algorithms for Visual Tasks.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models A Comprehensive Study of Class Incremental Learning Algorithms for Visual Tasks

Reference 20

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This paper cites Class-incremental learning: survey and performance evaluation on image classification.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Class-incremental learning: survey and performance evaluation on image classification

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This paper cites Incremental Learning of Object Detectors without Catastrophic Forgetting.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Incremental Learning of Object Detectors without Catastrophic Forgetting

Reference 22

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This paper cites In: Scott, D., Bel, N., Zong, C.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Scott, D., Bel, N., Zong, C

Reference 23

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MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: ICLR (2022)

Reference 24

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This paper cites Recent Advances of Continual Learning in Computer Vision: An Overview.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Recent Advances of Continual Learning in Computer Vision: An Overview

Reference 25

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This paper cites Neurocomputing469, 28–51 (2022).

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Neurocomputing469, 28–51 (2022)

Reference 26

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This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 27

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This paper cites In: Proceedings of the 30th ACM International Conference on Information & Knowledge Manage- ment.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Proceedings of the 30th ACM International Conference on Information & Knowledge Manage- ment

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MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Causal Incremental Graph Convolution for Recommender System Retraining

Reference 30

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This paper cites In: Proceedings of the 2nd Interna- tional Workshop on Deep Multimodal Gener- ation and Retrieval.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Proceedings of the 2nd Interna- tional Workshop on Deep Multimodal Gener- ation and Retrieval

Reference 31

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This paper cites ERAGent: Enhancing Retrieval-Augmented Language Models with Improved Accuracy, Efficiency, and Personalization.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models ERAGent: Enhancing Retrieval-Augmented Language Models with Improved Accuracy, Efficiency, and Personalization

Reference 32

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This paper cites LLM-based Medical Assistant Personalization with Short- and Long-Term Memory Coordination.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models LLM-based Medical Assistant Personalization with Short- and Long-Term Memory Coordination

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This paper cites In: Proceedings of the AAAI Symposium Series, vol.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Proceedings of the AAAI Symposium Series, vol

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MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models RecSys ’22, pp

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This paper cites A Practical Incremental Method to Train Deep CTR Models.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models A Practical Incremental Method to Train Deep CTR Models

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MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Incremental Learning for Personalized Recommender Systems

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This paper cites Incremental Factorization Machines for Persistently Cold-starting Online Item Recommendation.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Incremental Factorization Machines for Persistently Cold-starting Online Item Recommendation

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This paper cites In: User Modeling, Adaptation, and Personaliza- tion: 22nd International Conference, UMAP 2014, Aalborg, Denmark, July 7-11, 2014.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: User Modeling, Adaptation, and Personaliza- tion: 22nd International Conference, UMAP 2014, Aalborg, Denmark, July 7-11, 2014

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This paper cites Interna- tional Journal of Computer Vision129(6), 1789–1819 (2021).

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Interna- tional Journal of Computer Vision129(6), 1789–1819 (2021)

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This paper cites In: Com- puter Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part II 16, pp.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Com- puter Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part II 16, pp

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MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models iCaRL: Incremental Classifier and Representation Learning

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MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Online Continual Learning with Maximally Interfered Retrieval

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MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Psychology of Learning and Motivation vol

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This paper cites In: International Conference on Machine Learn- ing, pp.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: International Conference on Machine Learn- ing, pp

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This paper cites Advances in neural information processing systems30(2017).

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Advances in neural information processing systems30(2017)

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This paper cites In: European Conference on Information Retrieval, pp.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: European Conference on Information Retrieval, pp

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This paper cites In: Duh, K., Gomez, H., Bethard, S.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Duh, K., Gomez, H., Bethard, S

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This paper cites SLMRec: Distilling Large Language Models into Small for Sequential Recommendation.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models SLMRec: Distilling Large Language Models into Small for Sequential Recommendation

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MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Proceedings of the AAAI Conference on Artificial Intelli- gence, vol

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This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence44(7), 3366–3385 (2022) https://doi.org/10.1109/ TPAMI.2021.3057446.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models IEEE Transactions on Pattern Analysis and Machine Intelligence44(7), 3366–3385 (2022) https://doi.org/10.1109/ TPAMI.2021.3057446

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MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Data-centric Artificial Intelligence: A Survey

Reference 52

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MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Transactions on Machine Learning Research (2023)

Reference 53

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MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Revisiting Distillation and Incremental Classifier Learning

Reference 54

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MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: International Conference on Machine Learn- ing, pp

Reference 55

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MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Advances in Neural Information Processing Systems32(2019)

Reference 56

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MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Dataset Pruning: Reducing Training Data by Examining Generalization Influence

Reference 57

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MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models In: Proceedings of the 2022 International Conference on Manage- ment of Data

Reference 58

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MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Proceedings of the IEEE86(11), 2278–2324 (1998) https://doi.org/10.1109/5

Reference 59

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MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Selective and Collaborative Influence Function for Efficient Recommendation Unlearning

Reference 60

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Reference 61

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Reference 62

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Reference 165

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