【推荐系统】AAAI2022推荐系统论文集锦

机器学习初学者

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2022-01-23 18:55


2022年第36届人工智能顶级会议AAAI论文列表已经放出,此次会议共收到9251篇论文提交,其中9020篇论文被审稿。最终录取篇数为1349篇,录取率为可怜的15%由于境外疫情形势依然严峻,大会将在2月22日到3月1日在线上进行举办。

较之历年接受率来说,今年的录取率可以说是断崖式下跌。下图对2017年至今年的投稿量以及接受率进行了可视化,可以说今年的投稿量之多与接受率之低形成了鲜明的对比。

关于对顶级会议历年论文的分析与整理可点击下方链接:
与往年的惯例相同,我们分析了今年接收论文的标题,可以发现以下结论:
  • 深度学习技术仍然是比较火热的技术之一;

  • 对图数据的研究依然是大家关注的数据形式之一;

  • 自监督学习、半监督学习、多智能体、表示学习是大家主要使用的学习范式;

  • 机器学习应用如目标检测、文本分类、语义分割等是目前大家比较关注的方向。

完整版清单可从官网下载查看。

https://aaai.org/Conferences/AAAI-22/wp-content/uploads/2021/12/AAAI-22_Accepted_Paper_List_Main_Technical_Track.pdf

接下来,特意从1349篇论文中筛选出与推荐系统相关的15篇文章供大家欣赏(去年的推荐系统论文文章的比例为33/1692),提前领略学术前沿趋势与牛人的最新想法。

1. Meta-Learning for Online Update of Recommender Systems

Minseok Kim, Hwanjun Song, Yooju Shin, Dongmin Park, Kijung Shin, Jae-Gil Lee

https://minseokkim.net/publication/2022melon_aaai/2022melon_aaai.pdf

2. DiPS: Differentiable Policy for Sketching in Recommender Systems

Aritra Ghosh, Saayan Mitra, Andrew Lan

https://arxiv.org/pdf/2112.07616

3. Low-pass Graph Convolutional Network for Recommendation

Wenhui Yu, Zixin Zhang, Zheng Qin

4. Online certification of preference-based fairness for personalized recommender systems

Virginie Do, Sam Corbett-Davies, Jamal Atif, Nicolas Usunier

https://arxiv.org/pdf/2104.14527

5. Modeling Attrition in Recommender Systems with Departing Bandits

Omer Ben-Porat, Lee Cohen, Liu Leqi, Zachary Lipton, Yishay Mansour

6. A Dynamic Meta-Learning Model for Time-Sensitive Cold-Start Recommendations

Krishna P Neupane, Ervine Zheng, Yu Kong, Qi Yu

7. Context Uncertainty in Contextual Bandits with Applications to Recommender Systems

Hao Wang, Yifei Ma, Hao Ding, Yuyang Wan

8. Multi-view Intent Disentangle Graph Networks for Bundle Recommendation

Sen Zhao, Wei Wei, Ding Zou, Xian-Ling Mao

9. SMINet: State-Aware Multi-Aspect Interests Representation Network for Cold-Start Users Recommendation

Wanjie Tao, Yu Li, Liangyue Li, Zulong Chen, Hong Wen, Peilin Chen, Tingting Liang, Quan Lu

10. Leaping Through Time with Gradient-based Adaptation for Recommendation

Nuttapong Chairatanakul, Hoang NT, Xin Liu, Tsuyoshi Murata

https://arxiv.org/pdf/2112.05914

11. Cross-Task Knowledge Distillation in Multi-Task Recommendation

Chenxiao Yang, Junwei Pan, Xiaofeng Gao, Tingyu Jiang, Dapeng Liu, Guihai Chen

12. FPAdaMetric: False-positive-aware Adaptive Metric Learning for Session-based Recommendation

Jongwon Jeong, Jeong Choi, Hyunsouk Cho, Sehee Chung

13. Offline Interactive Recommendation with Natural-Language Feedback

Ruiyi Zhang, Tong Yu, Yilin Shen, Hongxia Jin

14. Learning the Optimal Recommendation from Explorative Users

Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu

https://arxiv.org/pdf/2110.03068

15. Obtaining Calibrated Probabilities with Personalized Ranking Models

Wonbin Kweon, SeongKu Kang, Hwanjo Yu

通过整理发现,此次会议接收的推荐系统相关论文主要涉及基于元学习的推荐系统2篇,序列化推荐5篇,基于强化学习的推荐系统4篇以及冷启动推荐2篇。

往期精彩回顾




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