201 citations
- Jingdong (China)CN6 papers
- University of PittsburghUS6 papers
- University of California, BerkeleyUS4 papers
- University of Science and Technology of ChinaCN4 papers
- Deutsches Elektronen-Synchrotron DESYDE3 papers
- European Organization for Nuclear ResearchCH3 papers
- Lawrence Berkeley National LaboratoryUS3 papers
- Stockholm UniversitySE3 papers
- Université Libre de BruxellesBE3 papers
- University of California, IrvineUS3 papers
- University of DelawareUS3 papers
- University of Wisconsin–MadisonUS3 papers
39 papers
Adaptive Experimentation with Delayed Binary Feedback
Zenan Wang, Carlos Carrion, Xiliang Lin +3
Conducting experiments with objectives that take significant delays to materialize (e.g. conversions, add-to-cart events, etc.) is challenging. Although the classical "split sample…
Sequential Search with Off-Policy Reinforcement Learning
Dadong Miao, Yanan Wang, Guoyu Tang +6
Recent years have seen a significant amount of interests in Sequential Recommendation (SR), which aims to understand and model the sequential user behaviors and the interactions be…
Spatial-Temporal Sequential Hypergraph Network for Crime Prediction with Dynamic Multiplex Relation Learning
Lianghao Xia, Chao Huang, Yong Xu +4
Crime prediction is crucial for public safety and resource optimization, yet is very challenging due to two aspects: i) the dynamics of criminal patterns across time and space, cri…
Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation
Chao Huang, Jiahui Chen, Lianghao Xia +6
Session-based recommendation plays a central role in a wide spectrum of online applications, ranging from e-commerce to online advertising services. However, the majority of existi…
AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization
Qingsong Zhang, Bin Gu, Cheng Deng +4
Vertical federated learning (VFL) is an effective paradigm of training the emerging cross-organizational (e.g., different corporations, companies and organizations) collaborative l…
Improving Contrastive Learning by Visualizing Feature Transformation
Rui Zhu, Bingchen Zhao, Jingen Liu +2
Contrastive learning, which aims at minimizing the distance between positive pairs while maximizing that of negative ones, has been widely and successfully applied in unsupervised…