Understanding and comparing scalable Gaussian process regression for big data

• المؤلفون الرئيسيون: Liu, Haitao, Cai, Jianfei, Ong, Yew-Soon, Wang, Yi
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2020
• الموضوعات: Engineering::Computer science and engineering; Gaussian Process; Big Data
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/139619
• المؤسسة: Nanyang Technological University

As a non-parametric Bayesian model which produces informative predictive distribution, Gaussian process (GP) has been widely used in various fields, like regression, classification and optimization. The cubic complexity of standard GP however leads to poor scalability, which poses challenges in the...