"Anomaly Detection"

Attention-Based Representation Learning for Time Series with Principal and Residual Space Monitoring
The encoder-decoder network is one of the most common deep learning models for time series representation learning and anomaly …
Botao Wang, Fugee Tsung, Hao Yan
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Adaptive Change Point Monitoring for High-Dimensional Data
In this paper, we propose a class of monitoring statistics for a mean shift in a sequence of high-dimensional observations. Inspired by …
Teng Wu, Runmin Wang, Hao Yan, Xiaofeng Shao
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Rapid Detection of Hot-Spots via Tensor Decomposition with Applications to Crime Rate Data
We propose an efficient statistical method (denoted as SSR-Tensor) to robustly and quickly detect hot-spots that are sparse and …
Yujie Zhao, Hao Yan, Sarah Holte, Yajun Mei
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Real-Time Detection of Clustered Events in Video-Imaging Data with Applications to Additive Manufacturing
The use of video-imaging data for in-line process monitoring applications has become more and more popular in the industry. In this …
Hao Yan, Marco Grasso, Kamran Paynabar, Bianca Maria Colosimo
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Toward a Better Monitoring Statistic for Profile Monitoring via Variational Autoencoders
Variational autoencoders have been recently proposed for the problem of process monitoring. While these works show impressive results …
Nurettin Dorukhan Sergin, Hao Yan
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Toward a Better Monitoring Statistic for Profile Monitoring via Variational Autoencoders
AKM2D: An Adaptive Framework for Online Sensing and Anomaly Quantification
In point-based sensing systems such as coordinate measuring machines and laser ultrasonics where complete sensing is impractical due to …
Hao Yan, Kamran Paynabar, Jianjun Shi
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Spatio-Temporal Anomaly Detection, Diagnostics, and Prediction of the Air-Traffic Trajectory Deviation Using the Convective Weather
With ahead-of-time aircraft management, we are able to re- duce aircraft collision and improve air traffic capacity. How- ever, there …
Xinyu Zhao, Hao Yan, Jing Li, Yutian Pang, Yongming Liu
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Rapid Detection of Hot-Spot by Tensor Decomposition with Application to Weekly Gonorrhea Data
In many bio-surveillance and healthcare applications, data sources are measured from many spatial locations repeatedly over time, say, …
Yujie Zhao, Hao Yan, Sarah E. Holte, Roxanne P. Kerani, Yajun Mei
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Weakly Correlated Profile Monitoring Based on Sparse Multi-Channel Functional Principal Component Analysis
Although several works have been proposed for multi-channel profile monitoring, two additional challenges are yet to be addressed: (i) …
Chen Zhang, Hao Yan, Seungho Lee, Jianjun Shi
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A Wavelet-Based Penalized Mixed-Effects Decomposition for Multichannel Profile Detection of In-Line Raman Spectroscopy
Modeling and analysis of profiles, especially high-dimensional nonlinear profiles, is an important and challenging topic in statistical …
Xiaowei Yue, Hao Yan, Jin Gyu Park, Zhiyong Liang, Jianjun Shi
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