Definition 1. A Gaussian Process is a collection of random variables, any finite number of which have (consistent) joint Gaussian distributions. 高斯分布(Gaussian Distribution) 是由方差向量(一维的时候是一个常量)和一个协方差矩阵(一维是方差)确定. 而高斯过程是一个随机过程的集合,它由一个均值函数m(x)和方差函数k(x,x')…
A Statistical View of Deep Learning (III): Memory and Kernels Memory, the ways in which we remember and recall past experiences and data to reason about future events, is a term used frequently in current literature. All models in machine learning co…
使用不同的机器学习方法进行预测 续上篇2_Linear Regression and Support Vector Regression 高斯过程回归 %matplotlib inline import requests from StringIO import StringIO import numpy as np import pandas as pd # pandas import matplotlib.pyplot as plt # module for plotting import…
虽然翻译水平有限,但是看原文虽然看得懂,但是在词汇的问题上,会导致看了后面忘了前面,所以先蹩脚的翻译成中文,然后在仔细思考论文的思想(当然不能翻译成中文就不看英文原本了,得两者一起看,这样不会丢失前面的思路,加快论文理解速度),我想随着不断的翻译,应该会提升效果吧.希望不会误导别人才好. sparse linear regression with beta process priors(2010) Bo Chen,John Paisley and Lawrence Carin 摘要:在beta处…
Introduction to Gaussian Processes Gaussian processes (GP) are a cornerstone of modern machine learning. They are often used for non-parametric regression and classification, and are extended from the theory behind Gaussian distributions and Gaussian…
