Spatio-temporal change-point detection and constrained Bayesian optimization

Change-point detection

Chen, Junzhuo ; Kim, Seong-Hee Xie, Yao Industrial and Systems Engineering Aral, Mustafa M. Paynabar, Kamran Shi, Jianjun ; Kim, Seong-Hee

University:Georgia Institute of Technology

Department:Industrial and Systems Engineering

关键词: Change-point detection;   

Others  :  https://smartech.gatech.edu/bitstream/1853/61247/1/CHEN-DISSERTATION-2019.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

This thesis makes contributions to two research topics: spatio-temporal change-point detection and constrained Bayesian optimization. Spatio-temporal change-point detection is concerned with detecting statistical anomalies based on multiple data streams collected at different locations. In Chapter 2 and Chapter 3, we address two challenges in spatio-temporal change-point detection: (i) how to deal with data with high dimensionality, and (ii) how to capture spatial and temporal correlations. Bayesian optimization is a prevalent approach for optimization problems defined by expensive-to-evaluate black-box functions. In Chapter 4, we develop a practical algorithm for optimization problems with black-box objective function and constraints.