Tensor-Based Temporal Control for Partially Observed High-Dimensional Streaming Data

References

• Boyd, S., Parikh, N., Chu, E., Peleato, B., and Eckstein, J. (2011), “Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers,” Foundations and Trends® in Machine Learning, 3, 1–122. DOI: 10.1561/2200000016.
   Google Scholar
• Chen, X., and Sun, L. (2020), “Low-Rank Autoregressive Tensor Completion for Multivariate Time Series Forecasting,” ArXiv: abs/2006.10436
   Google Scholar
• Chen, X., and Sun, L. (2021), “Bayesian Temporal Factorization for Multidimensional Time Series Prediction,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 44, 4659–4673. DOI: 10.1109/TPAMI.2021.3066551.
   Web of Science ®Google Scholar
• Gahrooei, M. R., Yan, H., Paynabar, K., and Shi, J. (2021), “Multiple Tensor-on-Tensor Regression: An Approach for Modeling Processes with Heterogeneous Sources of Data,” Technometrics, 63, 147–159. DOI: 10.1080/00401706.2019.1708463.
   Web of Science ®Google Scholar
• Gandy, S., Recht, B., and Yamada, I. (2011), “Tensor Completion and Low-n-Rank Tensor Recovery via Convex Optimization,” Inverse Problems, 27, 025010. DOI: 10.1088/0266-5611/27/2/025010.
   Web of Science ®Google Scholar
• Gaw, N., Yousefi, S., and Gahrooei, M. R. (2021), “Multimodal Data Fusion for Systems Improvement: A Review,” IISE Transactions, 54, 1098–1116. DOI: 10.1080/24725854.2021.1987593.
   Web of Science ®Google Scholar
• Gómez, A. M. E., Li, D., and Paynabar, K. (2022), “An Adaptive Sampling Strategy for Online Monitoring and Diagnosis of High-Dimensional Streaming Data,” Technometrics, 64, 253–269. DOI: 10.1080/00401706.2021.1967198.
   Web of Science ®Google Scholar
• Huang, B., Mu, C., Goldfarb, D., and Wright, J. (2015), “Provable Models for Robust Low-Rank Tensor Completion,” Pacific Journal of Optimization, 11, 339–364.
   Web of Science ®Google Scholar
• Kolda, T. G., and Bader, B. W. (2009), “Tensor Decompositions and Applications,” SIAM Review, 51, 455–500. DOI: 10.1137/07070111X.
   Web of Science ®Google Scholar
• Liu, J., Musialski, P., Wonka, P., and Ye, J. (2013), “Tensor Completion for Estimating Missing Values in Visual Data,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 35, 208–220. DOI: 10.1109/TPAMI.2012.39.
   PubMed Web of Science ®Google Scholar
• Llosa-Vite, C., and Maitra, R. (2023), “Reduced-Rank Tensor-on-Tensor Regression and Tensor-Variate Analysis of Variance,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 45, 2282–2296. DOI: 10.1109/TPAMI.2022.3164836.
   PubMed Web of Science ®Google Scholar
• Lock, E. F. (2018), “Tensor-on-Tensor Regression,” Journal of Computational and Graphical Statistics, 27, 638–647. DOI: 10.1080/10618600.2017.1401544.
   PubMed Web of Science ®Google Scholar
• Nesterov, Y. (1983), “A Method for Solving a Convex Programming Problem with Convergence Rate O(1/k2),” Soviet Mathematics Doklady, 27, 367–372.
   Google Scholar
• Thudumu, S., Branch, P., Jin, J., and Singh, J. (2020), “A Comprehensive Survey of Anomaly Detection Techniques for High Dimensional Big Data,” Journal of Big Data, 7, 1–30. DOI: 10.1186/s40537-020-00320-x.
   Google Scholar
• Wang, F., Gahrooei, M. R., Zhong, Z., Tang, T., and Shi, J. (2021), “An Augmented Regression Model for Tensors with Missing Values,” IEEE Transactions on Automation Science and Engineering, 19, 2968–2984. DOI: 10.1109/TASE.2021.3102953.
   Web of Science ®Google Scholar
• Wold, S., Esbensen, K., and Geladi, P. (1987), “Principal Component Analysis,” Chemometrics and Intelligent Laboratory Systems, 2, 37–52. DOI: 10.1016/0169-7439(87)80084-9.
   Web of Science ®Google Scholar
• Xiong, L., Chen, X., Huang, T. K., Schneider, J., and Carbonell, J. G. (2010), “Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization,” in Proceedings of the 2010 SIAM International Conference on Data Mining, pp. 211–222.
   Google Scholar
• Xue, J., Zhao, Y., Huang, S., Liao, W., Chan, J. C., and Kong, S. G. (2021), “Multilayer Sparsity-Based Tensor Decomposition for Low-Rank Tensor Completion,” IEEE Transactions on Neural Networks and Learning Systems, 33, 6916–6930. DOI: 10.1109/TNNLS.2021.3083931.
   Web of Science ®Google Scholar
• Yan, H., Paynabar, K., and Pacella, M. (2019), “Structured Point Cloud Data Analysis via Regularized Tensor Regression for Process Modeling and Optimization,” Technometrics, 61, 385–395. DOI: 10.1080/00401706.2018.1529628.
   Web of Science ®Google Scholar
• Yu, H., Rao, N., and Dhillon, I. S. (2016), “Temporal Regularized Matrix Factorization for High-Dimensional Time Series Prediction,” in Advances in Neural Information Processing Systems (Vol. 29).
   Google Scholar
• Zhang, Z., and Yang, L. (2021), “State-Based Opportunistic Maintenance with Multifunctional Maintenance Windows,” IEEE Transactions on Reliability, 70, 1481–1494. DOI: 10.1109/TR.2020.2995277.
   Web of Science ®Google Scholar
• Zhao, Q., Caiafa, C. F., Mandic, D. P., Chao, Z. C., Nagasaka, Y., Fujii, N., Zhang, Z., and Cichocki, A. (2013), “Higher Order Partial Least Squares (HOPLS): A Generalized Multilinear Regression Method,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 35, 1660–1673. DOI: 10.1109/TPAMI.2012.254.
   PubMed Web of Science ®Google Scholar
• Zhong, Z., Mou, S., Hunt, J. H., and Shi, J. (2022), “Finite Element Analysis Model-Based Cautious Automatic Optimal Shape Control for Fuselage Assembly,” ASME Journal of Manufacturing Science and Engineering, 144, 081009. DOI: 10.1115/1.4053501.
   Web of Science ®Google Scholar
• Zhong, Z., Paynabar, K., and Shi, J. (2023), “Image-Based Feedback Control Using Tensor Analysis,” Technometrics, 65, 305–314. DOI: 10.1080/00401706.2022.2157880.
   Web of Science ®Google Scholar
• Zhou, J., Sun, W. W., Zhang, J., and Li, L. (2021), “Partially Observed Dynamic Tensor Response Regression,” Journal of the American Statistical Association, 118, 424–439. DOI: 10.1080/01621459.2021.1938082.
   PubMed Web of Science ®Google Scholar