Summary of some machine learning Websites

Source: Internet
Author: User

Reposted from demonstrate's blog

Some common and
Websites related to machine learning are classified by topic.

Gaussian Processes

    • Http://www.gaussianprocess.org includes related books (books with Carl Edward Rasmussen), relatedProgramAnd the paper list of categories. This is also maintained by Carl himself. He should be
      GP introduced one of the earliest people in machine learning, Hinton student.

Nonparametric Bayesian methods

    • Http://www.cs.berkeley.edu /~ Jordan/npb.html is maintained by Jordan at the first glance. It mainly includes the Dirichlet process and other related random processes, how to perform Modeling in machine learning, and how to perform approximate inference. MainlyArticleList.

Probabilistic graphical model

    • Http://www.cs.ubc.ca /~ Murphyk/Bayes/bnintro.html is an introduction to Bayesian belief networks maintained by Kevin Murphy. It contains the most basic concepts, relevant literature, and links to software. The rare UCB is not a student of Jordan (the boss is
      Stuart Russel ).
    • Http://www.cs.berkeley.edu /~ Jordan/graphical.html is a compilation of Jordan's papers on this aspect.
    • Http://www.inference.phy.cam.ac.uk/hmw26/crf/ is about the collection of Conditional Random Fields papers and software, maintained by Hanna Wallach.

Compressed Sensing

    • Http://www-dsp.rice.edu/cs is the paper classification list maintained by Rice University, software links, etc. We recommend the tutorial written by Emmanuel candès, Who is David.
      Donoho student.

Tensor

    • Http://csmr.ca.sandia.gov /~ Tgkolda/pubs/index.html some math-biased articles about tensor.

Deep Belief Network

    • Http://www.cs.toronto.edu /~ Hinton/csc2515/deeprefs.html is the DBN reading list of machine learning courses offered by Geoffrey Hinton for graduate students.

Kernel Methods

    • Http://www.cs.berkeley.edu /~ Jordan/kernels.html is a list of articles maintained by Jordan about kernel methods.

Markov Logic

    • Http://ai.cs.washington.edu/pubs is the UW ai Group Article, which has a lot about Markov logic, because Pedro Domingos is the group.

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