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Hierarchical Gaussian Process Models for Improved Metamodeling., , , , and . ACM Trans. Model. Comput. Simul., 30 (4): 23:1-23:17 (2020)Experimental Evaluation of Machine Learning Methods for Robust Received Signal Strength-Based Visible Light Positioning., , , , and . Sensors, 20 (21): 6109 (2020)Active Learning for Feasible Region Discovery., , , and . ICMLA, page 567-572. IEEE, (2019)Deep Gaussian Process metamodeling of sequentially sampled non-stationary response surfaces., , , , and . WSC, page 1728-1739. IEEE, (2017)Indoor Person Identification Using a Low-Power FMCW Radar., , , , , , and . IEEE Trans. Geosci. Remote. Sens., 56 (7): 3941-3952 (2018)Indoor human activity recognition using high-dimensional sensors and deep neural networks., , , , , and . Neural Comput. Appl., 32 (16): 12295-12309 (2020)Machine Learning for RSS-Based Visible Light Positioning., , , , and . (May 2022)Structured Inference Networks Using High-Dimensional Sensors for Surveillance Purposes., , , , and . EANN, volume 893 of Communications in Computer and Information Science, page 16-27. Springer, (2018)Batch Bayesian Active Learning For Feasible Region Identification by Local Penalization., , , , and . WSC, page 2779-2790. IEEE, (2020)Data-Efficient Gaussian Process Regression for Accurate Visible Light Positioning., , , , and . IEEE Commun. Lett., 24 (8): 1705-1709 (2020)