【转】机器学习书单 - michen6/personal GitHub Wiki

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 Prediction

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, Optimization, 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 Learning)

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: 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 Implementation

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