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I was a university teacher, main interest areas:1、Spatio-temporal data analysis 2、Machine Learning3、 Pattern Recognition

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[转载]机器学习推荐书目  

2013-10-24 22:23:30|  分类: 默认分类 |  标签: |举报 |字号 订阅

  下载LOFTER 我的照片书  |
机器学习推荐书目

来源:水木社区人工智能版。

发信人: Insomnia (完美主义是种病), 信区: AI
标 题: Machine Learning书单
发信站: 水木社区 (Fri Mar 29 16:46:37 2013), 站内

持续更新,请补充。

除了以下推荐的书以外,出版在Foundations and Trends in Machine Learning上面的survey文章都值得一看。

入门:

Pattern Recognition And Machine Learning

Christopher M. Bishop

Machine Learning : A Probabilistic Perspective

Kevin P. Murphy

The Elements of Statistical Learning : Data Mining, Inference, and Predictio
n

Trevor Hastie, Robert Tibshirani, Jerome Friedman

Information Theory, Inference and Learning Algorithms

David J. C. MacKay

All of Statistics : A Concise Course in Statistical Inference

Larry Wasserman

优化:

Convex Optimization

Stephen Boyd, Lieven Vandenberghe

Numerical Optimization

Jorge Nocedal, Stephen Wright

Optimization for Machine Learning

Suvrit Sra, Sebastian Nowozin, Stephen J. Wright

核方法:

Kernel Methods for Pattern Analysis

John Shawe-Taylor, Nello Cristianini

Learning with Kernels : Support Vector Machines, Regularization, Optimizatio
n, and Beyond

Bernhard Schlkopf, Alexander J. Smola

半监督:

Semi-Supervised Learning

Olivier Chapelle

高斯过程:

Gaussian Processes for Machine Learning (Adaptive Computation and Machine Le
arning)

Carl Edward Rasmussen, Christopher K. I. Williams

概率图模型:

Graphical Models, Exponential Families, and Variational Inference

Martin J Wainwright, Michael I Jordan

Boosting:

Boosting : Foundations and Algorithms

Schapire, Robert E.; Freund, Yoav

贝叶斯:

Statistical Decision Theory and Bayesian Analysis

James O. Berger

The Bayesian Choice : From Decision-Theoretic Foundations to Computational I
mplementation

Christian P. Robert

Bayesian Nonparametrics

Nils Lid Hjort, Chris Holmes, Peter Müller, Stephen G. Walker

Principles of Uncertainty

Joseph B. Kadane

Decision Theory : Principles and Approaches

Giovanni Parmigiani, Lurdes Inoue

蒙特卡洛:

Monte Carlo Strategies in Scientific Computing

Jun S. Liu

Monte Carlo Statistical Methods

Christian P.Robert, George Casella

信息几何:

Methods of Information Geometry

Shun-Ichi Amari, Hiroshi Nagaoka

Algebraic Geometry and Statistical Learning Theory

Watanabe, Sumio

Differential Geometry and Statistics

M.K. Murray, J.W. Rice

渐进收敛:

Asymptotic Statistics

A. W. van der Vaart

Empirical Processes in M-estimation

Geer, Sara A. van de

不推荐:

Statistical Learning Theory

Vladimir N. Vapnik

Bayesian Data Analysis, Second Edition

Andrew Gelman, John B. Carlin, Hal S. Stern, Donald B. Rubin

Probabilistic Graphical Models : Principles and Techniques

Daphne Koller, Nir Friedman



本文引用地址:http://bbs.sciencenet.cn/blog-791749-733099.html 
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