本文从上述官网链接接收列表中筛选出与推荐系统、数据偏差以及图相关的论文供大家学习,其中与推荐系统有关的论文16篇。本次论文整理涉及到众多推荐系统领域的子方向,比如推荐系统中的嵌入表存放问题、算法选择问题、推荐系统中具有点击后信息的广义延迟反馈模型、用于训练推荐模型的缓存增强batch内重要性重采样问题、基于图卷积网络的推荐系统、推荐系统中的注入攻击分析、多样性推荐、基于自监督学习的推荐系统、大规模多用途的推荐系统数据集等。
其中部分论文已上传到Arxiv,大家可以自行下载进行阅读,也可以前往每周的论文周报进行查看。
| DreamShard: Generalizable Embedding Table Placement for Recommender Systems | ||||||
| RecZilla: Algorithm Selection for Recommender Systems | ||||||
| APG: Adaptive Parameter Generation Network for Click-Through Rate Prediction | ||||||
| Generalized Delayed Feedback Model with Post-Click Information in Recommender Systems | ||||||
| Cache-Augmented Inbatch Importance Resampling for Training Recommender Retriever | ||||||
| Graph Convolution Network based Recommender Systems: Learning Guarantee and Item Mixture Powered Strategy | ||||||
| Infinite Recommendation Networks: A Data-Centric Approach | ||||||
| Revisiting Injective Attacks on Recommender Systems | ||||||
| Diversified Recommendations for Agents with Adaptive Preferences | ||||||
| Debiased, Longitudinal and Coordinated Drug Recommendation through Multi-Visit Clinic Records | ||||||
| GBA: A Tuning-free Approach to Switch between Synchronous and Asynchronous Training for Recommendation Models | ||||||
| Recommender Forest for Efficient Retrieval | ||||||
| The trade-offs of model size in large recommendation models : A 10000 × compressed criteo-tb DLRM model (100 GB parameters to mere 10MB) | ||||||
| Contrastive Graph Structure Learning via Information Bottleneck for Recommendation | ||||||
| Tenrec: A Large-scale Multipurpose Benchmark Dataset for Recommender Systems | ||||||
| Incorporating Bias-aware Margins into Contrastive Loss for Collaborative Filtering |
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