15 citations · 51 across the 8 of their papers we have counts for
8 papers
High Dimensional Data Decomposition for Anomaly Detection of Textured Images
Ji Song, Xing Wang, Jianguo Wu +1
In the realm of diverse high-dimensional data, images play a significant role across various processes of manufacturing systems where efficient image anomaly detection has emerged…
Non-stationary and Sparsely-correlated Multi-output Gaussian Process with Spike-and-Slab Prior
Wang Xinming, Li Yongxiang, Yue Xiaowei +1
Multi-output Gaussian process (MGP) is commonly used as a transfer learning method to leverage information among multiple outputs. A key advantage of MGP is providing uncertainty q…
Regularized Multi-output Gaussian Convolution Process with Domain Adaptation
Wang Xinming, Wang Chao, Song Xuan +2
Multi-output Gaussian process (MGP) has been attracting increasing attention as a transfer learning method to model multiple outputs. Despite its high flexibility and generality, M…
Generalized Time Warping Invariant Dictionary Learning for Time Series Classification and Clustering
Ruiyu Xu, Chao Wang, Yongxiang Li +1
Dictionary learning is an effective tool for pattern recognition and classification of time series data. Among various dictionary learning techniques, the dynamic time warping (DTW…
Failure-averse Active Learning for Physics-constrained Systems
Cheolhei Lee, Xing Wang, Jianguo Wu +1
Active learning is a subfield of machine learning that is devised for design and modeling of systems with highly expensive sampling costs. Industrial and engineering systems are ge…
Partitioned Active Learning for Heterogeneous Systems
Cheolhei Lee, Kaiwen Wang, Jianguo Wu +2
Active learning is a subfield of machine learning that focuses on improving the data collection efficiency of expensive-to-evaluate systems. Especially, active learning integrated…
Neural Network Gaussian Process Considering Input Uncertainty for Composite Structures Assembly
Cheolhei Lee, Jianguo Wu, Wenjia Wang +1
Developing machine learning enabled smart manufacturing is promising for composite structures assembly process. To improve production quality and efficiency of the assembly process…
Online Structural Change-point Detection of High-dimensional Streaming Data via Dynamic Sparse Subspace Learning
Ruiyu Xu, Jianguo Wu, Xiaowei Yue +1
High-dimensional streaming data are becoming increasingly ubiquitous in many fields. They often lie in multiple low-dimensional subspaces, and the manifold structures may change ab…