Search Results for author: Chaochuan Hou

Found 2 papers, 2 papers with code

ADGym: Design Choices for Deep Anomaly Detection

1 code implementation • NeurIPS 2023 • Minqi Jiang, Chaochuan Hou, Ao Zheng, Songqiao Han, Hailiang Huang, Qingsong Wen, Xiyang Hu, Yue Zhao

Deep learning (DL) techniques have recently found success in anomaly detection (AD) across various fields such as finance, medical services, and cloud computing.

Anomaly Detection Cloud Computing

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Code

Weakly Supervised Anomaly Detection: A Survey

2 code implementations • 9 Feb 2023 • Minqi Jiang, Chaochuan Hou, Ao Zheng, Xiyang Hu, Songqiao Han, Hailiang Huang, Xiangnan He, Philip S. Yu, Yue Zhao

Anomaly detection (AD) is a crucial task in machine learning with various applications, such as detecting emerging diseases, identifying financial frauds, and detecting fake news.

Supervised Anomaly Detection Time Series +2

131

Paper
Code

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