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- Zhejiang UniversityCN23 papers
- Shanghai Jiao Tong UniversityCN13 papers
- Tsinghua UniversityCN13 papers
- Alibaba Group (United States)US11 papers
- University of Science and Technology of ChinaCN11 papers
- Peking UniversityCN10 papers
- CAS Key Laboratory of Urban Pollutant ConversionCN7 papers
- Nanyang Technological UniversitySG6 papers
- University of Electronic Science and Technology of ChinaCN6 papers
- Chinese Academy of SciencesCN5 papers
- Rutgers, The State University of New JerseyUS5 papers
- Singapore Management UniversitySG5 papers
35 papers · 1 filter
GraphAD: A Graph Neural Network for Entity-Wise Multivariate Time-Series Anomaly Detection
Xu Chen, Qiu Qiu, Changshan Li +1
In recent years, the emergence and development of third-party platforms have greatly facilitated the growth of the Online to Offline (O2O) business. However, the large amount of tr…
Meta-Weight Graph Neural Network: Push the Limits Beyond Global Homophily
Xiaojun Ma, Qin Chen, Yuanyi Ren +2
Graph Neural Networks (GNNs) show strong expressive power on graph data mining, by aggregating information from neighbors and using the integrated representation in the downstream…
MixSeq: Connecting Macroscopic Time Series Forecasting with Microscopic Time Series Data
Zhibo Zhu, Ziqi Liu, Ge Jin +4
Time series forecasting is widely used in business intelligence, e.g., forecast stock market price, sales, and help the analysis of data trend. Most time series of interest are mac…
Exponential Graph is Provably Efficient for Decentralized Deep Training
Bicheng Ying, Kun Yuan, Yiming Chen +3
Decentralized SGD is an emerging training method for deep learning known for its much less (thus faster) communication per iteration, which relaxes the averaging step in parallel S…
SAR-Net: A Scenario-Aware Ranking Network for Personalized Fair Recommendation in Hundreds of Travel Scenarios
Qijie Shen, Wanjie Tao, Jing Zhang +3
The travel marketing platform of Alibaba serves an indispensable role for hundreds of different travel scenarios from Fliggy, Taobao, Alipay apps, etc. To provide personalized reco…
Learning Effective and Efficient Embedding via an Adaptively-Masked Twins-based Layer
Bencheng Yan, Pengjie Wang, Kai Zhang +4
Embedding learning for categorical features is crucial for the deep learning-based recommendation models (DLRMs). Each feature value is mapped to an embedding vector via an embeddi…