![多任务学习中的跷跷板和负迁移现象](/attachments/WE3W5KDI.png)
Progressive Layered Extraction (PLE): A Novel Multi-Task Learning (MTL) Model for Personalized Recommendations
Alibaba Group 2020 RecSys | 用渐进式分层提取语义信息,解决推荐系统中的多任务问题
![AdaSparse overview. Figure 2 in paper.](/assets/posts/AdaSparse/overview.png)
AdaSparse: Learning Adaptively Sparse Structures for Multi-Domain Click-Through Rate Prediction
Alibaba Group 2022 CIKM | 稀疏的结构解决多场景的CTR预测任务
APG: Adaptive Parameter Generation Network for Click-Through Rate Prediction
Alibaba Group 2022 NIPS | 生成式的网络权重解决多场景的CTR预测任务
![STAR](/attachments/88C5FQ96.png)
One Model to Serve All: Star Topology Adaptive Recommender for Multi-Domain CTR Prediction
Alibaba Group 2021 CIKM | 共享和场景特定的星形网络解决多场景的CTR预测任务
![Preview Image](/attachments/AUA5SDVJ.png)
Attention is All you Need
Google 2017 NIPS | 从代码的角度详细解读Transformer
![The difference between existing attacks and PatchBackdoor.](/assets/posts/PatchBackdoor/compare.png)
PatchBackdoor: Backdoor Attack against Deep Neural Networks without Model Modification
Tsinghua 2023 WWW