Machine Learning Group - University of Waikato
Offers WEKA, a comprehensive, open-source (GPL) machine learning and data mining toolkit in Java with classification, regression, clustering, and association rules. Command-line and GUI interfaces.
Machine Learning Lab - The Hebrew University
Research projects on learning in human-machine interaction, natural language interface to the WWW, statistical analysis of neurophysiological data, self-organization of proteins, nonlinear acoustic signal processing.
Machine Learning Laboratory - UMass
Research on Neural Networks and Decision Trees.
Machine Learning Research Group - UTCS
Research on General Inductive Learning, Inductive Logic Programming, Natural Language Learning, Qualitative Modeling & Diagnosis, Learning for Planning and Problem Solving. Recommender Systems and Text Categorization Student Modeling for Intelligent Tutoring Systems Text Data Mining Theory and Knowledge Refinement.
Machine Learning Research Group - UW-Madison
Research on information retrieval and extraction, bioinformatics, connectionist models, hybrid systems.
The Machine Learning Systems Group at JPL
Applied research in data mining, knowledge discovery, pattern recognition, and automated classification and clustering.
Modeling network routing as Partially Observable Markov Decision Processes (POMDPs)
Uses partially observable Markov decision processes (POMDPs) as a basic framework for multi-agent planning
NCSA Automated Learning Group (ALG)
Archive of software, white papers, and research surveys maintained by a research lab at the National Center for Supercomputing Applications (NCSA)
The NeuroCOLT Project
ESPRIT working group on Neural and Computational Learning Theory. Partners, projects, publications archive.
Partially Observable Markov Decision Processes (POMDP)
Introduction by Hajime Fujita to POMDPs as a representation for multi-agent learning
Pattern Recognition and Image Processing (PRIP) Lab, Michigan State University
Develops algorithms and representations for efficient pattern matching. Applications include face recognition, fingerprint identification, image analysis, 3-D model construction and visualization, and robot navigation.
Probabilistic and Statistical Inference - University of Toronto
Research on computational machine learning tools and theoretical frameworks with applications in computational molecular biology, computer vision, sensory processing, and iterative decoding.
Robot Learning Laboratory - CMU
Research on Localization and Mapping, Partially Observable Markov Decision Processes, Computer Vision and Image Processing, Robot Architectures and Programming Languages, Learning Algorithms.
Soft Computing in Machine Learning
Applications of soft computing (fuzzy systems, neural networks, and genetic algorithms) in machine learning. Manuscripts and MATLAB codes related to fuzzy clustering and classification, and visualization and analysis of high-dimensional data.
Software Competence Center, Hagenberg (SCCH): Division of Knowledge Based Technologies
Knowledge-based concepts, tools, and methods, and their applications, including: fuzzy systems, neural networks, genetic algorithms, machine learning, and natural language processing.
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