due to the distributed training paradigm, FedRec is vulnerable to model poisoning attacks. In this paper, we focus on the targeted model poisoning attack against FedRec, which aims at effectively attacking the FedRec via uploading poisoned gradients to raise...
In this paper, we treat a user's possible behaviors and the potential interacting item categories as the user's intent. And we aim to study how to fuse candidate item lists generated from different objectives aware of user intents. To address such a task, we propose an Intent-aware ranking...
(主要是我自己准备看的,你们可以到full paper里自己找找自己的需求) Graph Transformer for Recommendation #港大&华工 # 自监督学习 传统的自监督方法虽然效果不错,但是存在监督信号质量差,噪声抵抗能力弱等问题。文章提出一个新的模型以缓解相关问题 A Critical Reexamination of Intra-List Distance and Dispersion...
hyperbolic space modeling has recently been introduced into collaborative filtering methods. Among them, hyperbolic GCN combines the advantages of GCN and hyperbolic space and achieves a surprising performance. However, these methods only partially exploit the nature of hyperbolic space in...
大会概况：2023年的SIGIR计划于7月2327日在台北召开。大会设有多个投稿轨道，以满足不同学者的投稿需求。投稿将于近期截止，具体截止日期可查看大会官网。国内学者角色：中科大何向南教授：担任Short Paper Chair。中科院计算所郭嘉丰研究员：担任Reproducibility Paper Chair。中国人大宋睿华副教授：担任Tutorial ...
[SIGIR 2023 Oral] This is our Pytorch implementation for the paper: "Meta-optimized Contrastive Learning for Sequential Recommendation". - QinHsiu/MCLRec
[SIGIR 2023] This is the official PyTorch implementation for the paper: "EulerNet: Adaptive Feature Interaction Learning via Euler’s Formula for CTR Prediction". - Ethan-TZ/EulerNet
4. When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback? SIGIR2023 5. Multidimensional Fairness in Paper Recommendation 6. Leveraging Language Representation for Material Recommendation, Ranking, and Exploration ...
12. Graph Transformer for Recommendation, SIGIR2023 Chaoliu Li, Lianghao Xia, Xubin Ren, Yaowen Ye, Yong Xu, Chao Huang https://arxiv.org/abs/2306.02330 This paper presents a novel approach to representation learning in recommender systems by integrating generative self-supervised learning with gra...
本届SIGIR计划于2023年7月23-27日在台北举办。大会共设置3位General Chairs,其中有两位学者来自台大。 大陆学者也在本次大会中担任多个重要角色,中科大何向南教授担任Short Paper Chair,中科院计算所郭嘉丰研究员担任Reproducibility Paper Chair,中国人大宋睿华副教授担任Tutorial Chair,杭州城市学院明朝燕副教授担任SIRIP ...