http://www.cs./people/
http://pages.cs./~jerryzhu/
http://www.kyb.tuebingen./~chapelle
http://people.cs./~xiaofei/
http://www.cs./homes/dengcai2/
http://www.kyb./~bs
http://research.microsoft.com/~denzho/
http://www-users.cs./~kumar/dmbook/index.php#item5 (resources for the book of the introduction of data mining by Pang-ning Tan et.al. )(国内已经有相应的中文版)
http://www.cs./~roweis/lle/publications.html (lle算法源代码及其相关论文)
http://dataclustering.cse./index.html#software(data clustering)
http://www.cs./~roweis/ (里面有好多资源)
http://www.cse./~lawhiu/ (manifold learning)
http://www.math./~wittman/mani/ (manifold learning demo in matlab)
http://www.iipl.fudan.edu.cn/~zhangjp/literatures/MLF/INDEX.HTM (manifold learning in matlab)
http:///mlss05us_belkin_sslmm/ (semi supervised learning with manifold method by Belkin)
http://isomap./ (isomap主页)
http://web./cocosci/josh.html MIT TENENBAUM J B主页
http://web.engr./~tgd/ (国际著名的人工智能专家 Thomas G. Dietterich)
http://www.cs./~jordan/ (MIchael I.Jordan)
http://www.cs./~awm/ (Andrew W. Moore's homepage)
http://learning.cs./ (加拿大多伦多大学机器学习小组)
http://www.cs./~tom/ (Tom Mitchell,里面有与教材匹配的slide。)
Kernel Methods
|
Alexander J. Smola
Maximum Mean Discrepancy (MMD), Hilbert-Schmidt Independence Criterion (HSIC)
Bernhard Sch?lkopf
Kernel PCA
James T Kwok
Pre-Image, Kernel Learning, Core Vector Machine(CVM)
Jieping Ye
Kernel Learning, Linear Discriminate Analysis, Dimension Deduction
|
Multi-Task Learning
|
Andreas Argyriou
Multi-Task Feature Learning
Charles A. Micchelli
Multi-Task Feature Learning, Multi-Task Kernel Learning
Massimiliano Pontil
Multi-Task Feature Learning
Yiming Ying
Multi-Task Feature Learning, Multi-Task Kernel Learning
|
Semi-supervised Learning
|
Partha Niyogi
Manifold Regularization, Laplacian Eigenmaps
Mikhail Belkin
Manifold Regularization, Laplacian Eigenmaps
Vikas Sindhwani
Manifold Regularization
Xiaojin Zhu
Graph-based Semi-supervised Learning
|
Multiple Instance Learning
|
Sally A Goldman
EM-DD, DD-SVM, Multiple Instance Semi Supervised Learning(MISS)
|
Dimensionality Reduction
|
Neil Lawrence
Gaussian Process Latent Variable Models (GPLVM)
Lawrence K. Saul
Maximum Variance Unfolding(MVU), Semidefinite Embedding(SDE)
|
Machine Learning
|
Michael I. Jordan
Graphical Models
John Lafferty
Diffusion Kernels, Graphical Models
Daphne Koller
Logic, Probability
Zhang Tong
Theoretical Analysis of Statistical Algorithms, Multi-task Learning, Graph-based Semi-supervised Learning
Zoubin Ghahramani
Bayesian approaches to machine learning
Machine Learning @ Toronto
|
Statitiscal Machine Learning & Optimization
|
Jerome H Friedman
GLasso, Statistical view of AdaBoost, Greedy Function Approximation
Thevor Hastie
Lasso
Stephen Boyd
Convex Optimization
C.J Lin
Libsvm
|
http://www.dice./mlg/
半监督流形学习(流形正则化)
http://manifold.cs./
模式识别和神经网络工具箱
http://www.ncrg./netlab/index.php
机器学习开源代码
http:///software/tags/large-scale-learning/
统计学开源代码
http://www./
matlab各种工具箱链接
http://www.tech./spmc/links/matlab/matlab_toolbox.html
统计学学习经典在线教材
http://www./
机器学习开源源代码
http:///software/language/matlab/
From:http://tzczsq.blog.163.com/blog/static/22603058201102602452399/
http://www.cnblogs.com/skyseraph/