文件名称：Gaussian Processes for Machine Learning
文件大小：3.86MB
文件格式：PDF
更新时间：2013-03-15 00:23:59
Machine Learning
The goal of building systems that can adapt to their environments and learn from their experience has attracted researchers from many fields, including com- puter science, engineering, mathematics, physics, neuroscience, and cognitive science. Out of this research has come a wide variety of learning techniques that have the potential to transform many scientific and industrial fields. Recently, several research communities have converged on a common set of issues sur- rounding supervised, unsupervised, and reinforcement learning problems. The MIT Press series on Adaptive Computation and Machine Learning seeks to unify the many diverse strands of machine learning research and to foster high quality research and innovative applications.