Learning an Adaptive Meta Model-Generator for Incrementally Updating Recommender Systems

Author:

Peng Danni1,Pan Sinno Jialin2,Zhang Jie2,Zeng Anxiang3

Affiliation:

1. Nanyang Technological University, Singapore

2. School of Computer Science and Engineering Nanyang Technological University, Singapore

3. NTU SCSE, Singapore

Funder

Alibaba-NTU Singapore Joint Research Institute

Publisher

ACM

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. LiMAML: Personalization of Deep Recommender Models via Meta Learning;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

2. IncMSR: An Incremental Learning Approach for Multi-Scenario Recommendation;Proceedings of the 17th ACM International Conference on Web Search and Data Mining;2024-03-04

3. Dual-Memory and Knowledge-Aware Aggregation for Continual Knowledge Evolution in Federated Learning;2024

4. Agriculture Recommender System for Precision Farming using Machine Learning(ARS);2023 3rd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA);2023-12-21

5. An Incremental Update Framework for Online Recommenders with Data-Driven Prior;Proceedings of the 32nd ACM International Conference on Information and Knowledge Management;2023-10-21

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