activity
20192023
most citedTime-Series Anomaly Detection Service at Microsoft

588 citations · 691 across the 16 of their papers we have counts for

collaborators
Showing 2020Show all

5 papers · 1 filter

cs.CL2020★ 1 cited

AutoADR: Automatic Model Design for Ad Relevance

Yiren Chen, Yaming Yang, Hong Sun +7

Large-scale pre-trained models have attracted extensive attention in the research community and shown promising results on various tasks of natural language processing. However, th…

cs.LG2020★ 30 cited

Multivariate Time-series Anomaly Detection via Graph Attention Network

Hang Zhao, Yujing Wang, Juanyong Duan +7

Anomaly detection on multivariate time-series is of great importance in both data mining research and industrial applications. Recent approaches have achieved significant progress…

cs.LG2020★ 5 cited

Automated Model Selection for Time-Series Anomaly Detection

Yuanxiang Ying, Juanyong Duan, Chunlei Wang +3

Time-series anomaly detection is a popular topic in both academia and industrial fields. Many companies need to monitor thousands of temporal signals for their applications and ser…

cs.CV2020★ 20 cited

Mucko: Multi-Layer Cross-Modal Knowledge Reasoning for Fact-based Visual Question Answering

Zihao Zhu, Jing Yu, Yujing Wang +3

Fact-based Visual Question Answering (FVQA) requires external knowledge beyond visible content to answer questions about an image, which is challenging but indispensable to achieve…

cs.CL2020★ 19 cited

LadaBERT: Lightweight Adaptation of BERT through Hybrid Model Compression

Yihuan Mao, Yujing Wang, Chufan Wu +6

BERT is a cutting-edge language representation model pre-trained by a large corpus, which achieves superior performances on various natural language understanding tasks. However, a…