大牛们的blog （人工智能与机器学习）

大牛们的blog （人工智能与机器学习） - xiaxiazls的专栏 - 博客频道 - CSDN.NET
http://blog.csdn.net/xiaxiazls/article/details/7237373

大牛们的blog （人工智能与机器学习）国外人工智能界牛人主页以前转过一个计算机视觉领域内的牛人简介，现在转一个更宽范围内的牛人简介：http://people.cs.uchicago.edu/_{niyogi/http://www.cs.uchicago.edu/people/http://pages.cs.wisc.edu/}jerryzhu/http://www.kyb.tuebingen.mpg.de/_{chapellehttp://people.cs.uchicago.edu/}xiaofei/http://www.cs.uiuc.edu/homes/dengcai2/http://www.kyb.mpg.de/_{bshttp://research.microsoft.com/}denzho/http://www-users.cs.umn.edu/~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.toronto.edu/~roweis/lle/publications.html (lle算法源代码及其相关论文)http://dataclustering.cse.msu.edu/index.html#software（data clustering）http://www.cs.toronto.edu/~roweis/ (里面有好多资源)http://www.cse.msu.edu/~lawhiu/ (manifold learning)http://www.math.umn.edu/~wittman/mani/ (manifold learning demo in matlab)http://www.iipl.fudan.edu.cn/~zhangjp/literatures/MLF/INDEX.HTM (manifold learning in matlab)http://videolectures.net/mlss05us_belkin_sslmm/ (semi supervised learning with manifold method by Belkin)http://isomap.stanford.edu/ (isomap主页)http://web.mit.edu/cocosci/josh.html MIT TENENBAUM J B主页http://web.engr.oregonstate.edu/~tgd/ （国际著名的人工智能专家 Thomas G. Dietterich）http://www.cs.berkeley.edu/~jordan/ （MIchael I.Jordan）http://www.cs.cmu.edu/~awm/ (Andrew W. Moore's homepage)http://learning.cs.toronto.edu/ （加拿大多伦多大学机器学习小组）http://www.cs.cmu.edu/~tom/ （Tom Mitchell，里面有与教材匹配的slide。）Kernel MethodsAlexander J. SmolaMaximum Mean Discrepancy (MMD), Hilbert-Schmidt Independence Criterion (HSIC)Bernhard SchölkopfKernel PCAJames T KwokPre-Image, Kernel Learning, Core Vector Machine(CVM)Jieping YeKernel Learning, Linear Discriminate Analysis, Dimension DeductionMulti-Task LearningAndreas ArgyriouMulti-Task Feature LearningCharles A. MicchelliMulti-Task Feature Learning, Multi-Task Kernel LearningMassimiliano PontilMulti-Task Feature LearningYiming YingMulti-Task Feature Learning, Multi-Task Kernel LearningSemi-supervised LearningPartha NiyogiManifold Regularization, Laplacian EigenmapsMikhail BelkinManifold Regularization, Laplacian EigenmapsVikas SindhwaniManifold RegularizationXiaojin ZhuGraph-based Semi-supervised LearningMultiple Instance LearningSally A GoldmanEM-DD, DD-SVM, Multiple Instance Semi Supervised Learning(MISS)Dimensionality ReductionNeil LawrenceGaussian Process Latent Variable Models (GPLVM)Lawrence K. SaulMaximum Variance Unfolding(MVU), Semidefinite Embedding(SDE)Machine LearningMichael I. JordanGraphical ModelsJohn LaffertyDiffusion Kernels, Graphical ModelsDaphne KollerLogic, ProbabilityZhang TongTheoretical Analysis of Statistical Algorithms, Multi-task Learning, Graph-based Semi-supervised LearningZoubin GhahramaniBayesian approaches to machine learningMachine Learning @ TorontoStatitiscal Machine Learning & OptimizationJerome H FriedmanGLasso, Statistical view of AdaBoost, Greedy Function ApproximationThevor HastieLassoStephen BoydConvex OptimizationC.J LinLibsvm http://www.dice.ucl.ac.be/mlg/半监督流形学习（流形正则化）http://manifold.cs.uchicago.edu/模式识别和神经网络工具箱http://www.ncrg.aston.ac.uk/netlab/index.php机器学习开源代码http://mloss.org/software/tags/large-scale-learning/统计学开源代码http://www.wessa.net/matlab各种工具箱链接http://www.tech.plym.ac.uk/spmc/links/matlab/matlab_toolbox.html统计学学习经典在线教材http://www.statistics4u.info/机器学习开源源代码http://mloss.org/software/language/matlab/复制搜索