WWW 2020关于深度推荐系统与CTR预估相关的论文

Posted 2021-04-24 深度传送门

导读： 本文主要简要列举下Google、Facebook、Alibaba以及Tencent等各大公司在WWW 2020上关于深度推荐系统与CTR预估相关的论文。

1. Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems Wang-Cheng Kang (UC San Diego), Derek Zhiyuan Cheng (Google), Ting Chen (Google), Xinyang Yi (Google), Dong Lin (Google), Lichan Hong (Google), Ed H. Chi (Google)

2. Adversarial Multimodal Representation Learning for Click-Through Rate Prediction Xiang Li (Alibaba Group), Chao Wang (Alibaba Group), Jiwei Tan (Alibaba Group), Xiaoyi Zeng (Alibaba Group), Dan Ou (Alibaba Group), Bo Zheng (Alibaba Group)

论文：https://arxiv.org/abs/2003.07162

3. Off-policy Learning in Two-stage Recommender Systems Jiaqi Ma (University of Michigan), Zhe Zhao (Google AI), Xinyang Yi (Google AI ), Ji Yang (Google AI), Minmin Chen (Google AI), Jiaxi Tang (Simon Fraser University), Lichan Hong (Google AI), Ed H. Chi (Google AI)

4. Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation Mengyue Yang (University of Chinese Academy of Sciences), Qingyang Li (Didi Chuxing), Zhiwei Qin (Didi Chuxing), Jieping Ye (Didi Chuxing)

5. Jointly Learning to Recommend and Advertise Xiangyu Zhao (Michigan State University), Xudong Zheng (Bytedance), Xiwang Yang (Bytedance), Xiaobing Liu (Bytedance), Jiliang Tang(Michigan State University)

6. Beyond Clicks: Modeling Multi-Relational Item Graph for Session-Based Target Behavior Prediction Wen Wang (East China Normal University), Wei Zhang (East China Normal University), Shukai Liu (Tencent), Qi Liu (Tencent), Bo Zhang (Tencent), Leyu Lin (Tencent), Hongyuan Zha (Georgia Institute of Technology)

7. Field-aware Calibration: A Simple and Empirically Strong Method for Reliable Probabilistic Predictions Feiyang Pan (Chinese Academy of Sciences), Xiang Ao (Chinese Academy of Sciences), Pingzhong Tang (Tsinghua University), Min Lu (Tencent), Dapeng Liu (Tencent), Lei Xiao (Tencent), Qing He (Chinese Academy of Sciences)

8. LightRec: a Memory and Search-Efficient Recommender System Defu Lian (University of Science and Technology of China) , Haoyu Wang (University at Buffalo) , Zheng Liu (Microsoft Research Asia) , Jianxun Lian (Microsoft Research Asia), Enhong Chen (University of Science and Technology of China) , Xing Xie (Microsoft Research Asia)

9. Efficient Neural Interaction Function Search for Collaborative Filtering Quanming Yao (4Paradigm Inc), Xiangning Chen (UCLA), James Kwok (HKUST), Yong Li (Tsinghua University), Cho-Jui Hsieh (UCLA)

本文中涉及到的所有论文以及更多最前沿的推荐广告方面的论文分享请移步如下的GitHub项目进行学习交流、star以及fork，后续仓库会持续更新最新论文。

https://github.com/imsheridan/DeepRec

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