Machine Learning Network Online Information Service:
The MLnet OiS offers software, datasets, information about events,
research groups, persons and other interesting stuff related to
machine learning, knowledge discovery, case-based reasoning,
knowledge acquisition, and data mining.
http://www.mlnet.org
Online Machine Learning Resources:
Provided by the ML Group at the Austrian Research Institute for
Artificial Intelligence (OFAI).
http://www.ai.univie.ac.at/oefai/ml/ml-resources.html
Machine Learning at AAAI:
Starting point for online machine learning resources. Provided by
the American Association for Artificial Intelligence.
http://www.aaai.org/Pathfinder/html/machine.html
Kernel machines:
A central information source for the area of Support Vector
Machines, Gaussian Process prediction, Mathematical Programming with
Kernels, Regularization Networks, Reproducing Kernel Hilbert Spaces,
and related methods. Provides links to papers, upcoming events,
datasets, code.
http://www.kernel-machines.org
Computational Learning Theory:
A research field devoted to studying the design and analysis of
algorithms for making predictions about the future based on past
experiences. The emphasis in COLT is on rigorous mathematical
analysis. COLT is largely concerned with computational and data
efficiency.
http://www.learningtheory.org/
Reinforcement Learning Repository:
A centralized resource for researchers of reinforcement learning.
Maintained at Michigan State University.
http://www.cse.msu.edu/rlr/
Boosting research:
A website on Boosting and related ensemble learning methods.
Provided links to papers, upcoming events, datasets, and code.
http://www.boosting.org/
Mixture Modelling page:
Mixture modelling, Clustering, Intrinsic classification,
Unsupervised learning and Mixture modeling. Links and bibliography.
http://www.cs.monash.edu.au/~dld/mixture.modelling.page.html
Gowachin:
A competition on Grammatical Inference.
http://www.irisa.fr/Gowachin/
Machine Learning in Games:
How computers can learn to get better at playing games. This site is
for artificial intelligence researchers and intrepid game
programmers. I describe game programs and their workings; they rely
on heuristic search algorithms, neural networks, genetic algorithms,
temporal differences, and other methods.
http://satirist.org/learn-game/
Machine Learning FAQ:
Questions and answers about Machine Learning. Anyone can post
his/her own questions and answers.
http://recursive-partitioning.com/mlfaq/
ILPnet2:
Network of Excellence in Inductive Logic Programming.
http://www.cs.bris.ac.uk/~ILPnet2/
David W. Aha: Machine Learning Page:
Comprehensive machine learning resources from Applications to
Tutorials.
http://www.aic.nrl.navy.mil/~aha/research/machine-learning.html
Grammatical Inference:
Repository of information on grammatical inference, automata
induction, and language acquisition.
http://www.cs.iastate.edu/~honavar/gi/gi.html
Pattern Recognition Information:
A hub for Pattern Recognition linking to journals, books,
bibliographies, jobs, conferences and news.
http://www.ph.tn.tudelft.nl/PRInfo/index.html
Programming by Example:
Programming by example (or by demonstration) is a technique for
teaching the computer new behavior by demonstrating actions on
concrete examples. The system records user actions and generalizes a
program that can be used in new examples.
http://lieber.www.media.mit.edu/people/lieber/PBE/index.html
Recursive-Partitioning.com:
Comprehensive archive of bibliographies, FAQ lists, tutorials, and
other resources for supervised and unsupervised learning
http://www.recursive-partitioning.com
Machine learning for user modeling:
Resources for researchers and practitioners interested in the use of
learning techniques in intelligent, user-adaptive systems.
http://athos.rutgers.edu/ml4um/
