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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.