Machine Learning and Inference Laboratory - GMU
Research on Theories of Learning, Inference, and Discovery Data Mining and Knowledge Discovery, User Modeling and Intrusion Detection, Non-Darwinian Evolutionary Computation, Machine Vision through Learning, Education.

Machine Learning Group - UCI
Research at UCI spans the spectrum of models for learning, including those based on statistics, logic, mathematics, neural structures, information theory, and heuristic search algorithms.

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.

Artificial Intelligence Research Laboratory - Iowa State University
Resarch related to machine learning includes neural networks, automata induction, computational learning theory, data mining, knowledge discovery, bioinformatics.

Cognitive Computation, Harvard University
The group develops theories and systems pertaining to intelligent behavior using a unified methodology. At the heart of the approach is the idea that learning has a central role in intelligence.

Intelligent Data Analysis Group at GMD FIRST
The IDA group is concerned with learning systems for intelligent data analysis. In particular, we are developing tools for high-dimensional multivariate statistics based on methods originally developed in the field of statistics and, more recently, in the neural networks and machine learning community.

Cognitive Computation Group at UIUC
Developing theories and systems pertaining to intelligent behavior using a unified methodology. At the heart of the approach is the idea that learning has a central role in intelligence.

Machine learning and Neural Networks group - Universities of Florence, Pisa, and Siena
Research on adaptive processing of data structures, document analysis and technologies, natural language, machine learning for the web, visual databases, biochemistry and bioinformatics.

Machine Learning and Natural Language Processing Lab - Freiburg (Germany)
Research on Data Mining, Machine Learning,Inductive Logic Programming, Relational Learning, Machine Learning for Bioinformatics.

Machine Learning - ÖFAI
Information on their members, research areas, publications, teaching, and resources. Focus is on: data mining and knowledge discovery in databases, inductive logic programming, knowledge intensive learning, concept drift and context-sensitive learning, minimum description length principle, machine learning and music.

Computational Intelligence Group - University of Bristol
Research on kernel methods, support vector machines, neural networks, machine vision, bioinformatics, computational learning theory.

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.

Learning Lab at CMU, School of Computer Science
Software systems that learn user preferences, Robot learning, text learning, generic learning methods.

Machine Learning Research Group - UW-Madison
Research on information retrieval and extraction, bioinformatics, connectionist models, hybrid systems.

Machine Learning and Genetic Algorithms group - University of Turin
Research on learning first-order classification rules, first-order concept descriptions, genetic algorithms, neural networks, computational learning theory.

Institute for Process Control and Robotics - University of Karlsruhe (Germany)
Research on Machine Learning in Robotics, Factory Automation, and Assistance Systems.

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.

IDIAP machine Learning Group - Martigny (Switzerland)
Research on Support Vector Machines, Hidden Markov Models, fusion of generative and discriminative approaches, logical data analysis, large scale data analysis.

Gatsby Computational Neuroscience Unit - University College London
Research on neural computational theories of perception and action, with an emphasis on learning.

The Auton Project
Research on Data Mining, Active Learning & Exploration, Reinforcement Learning for Decision and Control.

LISA - Adaptive Computer Systems Laboratory - Université de Montréal
Research on modeling high-dimensional data, learning hyper-parameters, boosting of neural networks, Markovian models, data mining, and other areas related to neural networks.

Machine Learning Laboratory - UMass
Research on Neural Networks and Decision Trees.

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.

Knowledge Acquisition & Machine Learning Lab - University of Bari
Research on symbolic and numerical approaches to machine learning, first order logic, intelligent document processing, spatial data mining, human-computer interaction.

Machine Learning Group - Stockholm University
Research on inductive logic programming for natural language processing and for knowledge discovery in databases.

Computational Learning - Royal Holloway, University of London
Research on machine learning theory, kernel methods for text analysis, support vector machines, kernel theory.

Center for Automated Learning and Discovery - CMU
Large group with projects in robot learning, data mining for manufacturing and in multimedia databases, causal inference, and disclosure limitation.

Machine Learning at the Katholieke Universiteit Leuven
Research in Data mining, Inductive Logic Programming, Learning In Agents.

Center for Biological and Computational Learning - MIT
Research on theory of learning, neuroscience, bioinformatics & functional genomics, information extraction in text & multimedia, object detection/recognition, man-machines interfaces, virtual financial markets.

Machine Learning Group - University of Bristol
Research on higher-order concept learning, inductive logic programming, multi-agent learning systems, integration of prior knowledge, induction and deduction, incremental learning, hybrid symbolic/connectionist approaches, evolutionary strategies.

Knowledge Acquisition and Machine Learning Group - University of Ottawa
Research projects mainly focused on text: Intelligent Information Access, Text Summarization, Text Analysis for Knowledge Acquisition.

The Machine Learning Systems Group at JPL
Applied research in data mining, knowledge discovery, pattern recognition, and automated classification and clustering.

Automated Learning Group - NASA
Research projects on collective intelligence, surface modeling, autoclass, Bayesian search.

Computational Biology Group - University of Wales
Techniques include inductive logic programming, model based reasoning, evolutionary computing, neural networks, multivariate statistics. Applications to drig design, protein secondary structure prediction, functional genomics, etc.

Bioinformatics and Learning Metrics group - Helsinki University of Technology
Analysis of functional genomics data, Construction of data-dependent metrics for focusing data analysis on relevant or important aspects of the data.

Freiburg Recognition of ON-line HANDwriting (Frog On Hand)
An on-line handwriting recognition engine based upon statistical dynamic time warping (SDTW) and support vector machines with a Gaussian DTW kernel (SVM-GDTW).

Group Method of Data Handling (GMDH)
Tutorials, software, online books and articles on forecasting and systems modeling, optimization in expert systems, pattern recognition, data mining and knowledge discovery, from a research group at the Glushkov Institute of Cybernetics.

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)

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.

Intelligent Systems, University College London
Focuses on theory of logic and learning, and applied intelligent systems. Methodolgies range from traditional knowledge-based systems and neural networks to machine learning, agents, and evolutionary computation.

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.

Machine Learning at UC Santa Cruz
Research on decision theory, neural networks, computational biology, computational geometry, theoretical computer science, on-line learning algorithms, computational learning theory, reinforcement learning.

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

The NeuroCOLT Project
ESPRIT working group on Neural and Computational Learning Theory. Partners, projects, publications archive.

Computational Intelligence, Learning, & Discovery
Pursues research on algorithms and software tools for gleaning knowledge from data and their applications in Bioinformatics, Security Informatics, Medical Informatics, Geoinformatics, Chemical Informatics, Semantic Web, e-Government, e-Enterprises, e-Commerce, and e-Science.

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.

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.

Alberta Ingenuity Centre for Machine Learning (AICML)
Promotes curiosity-driven Machine Learning research, and leading edge scientific and commercial applications in the bioinformatics and interactive entertainment industries.