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.
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.
Columbia University Center for Computational Learning Systems (CCLS)
CCLS investigates machine learning and data mining and their application to natural language understanding, the World Wide Web, bioinformatics, systems security and other emerging areas.
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.
Computational Intelligence Group - University of Bristol
Research on kernel methods, support vector machines, neural networks, machine vision, bioinformatics, computational learning theory.
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.
Computational Learning - Royal Holloway, University of London
Research on machine learning theory, kernel methods for text analysis, support vector machines, kernel theory.
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).
Gatsby Computational Neuroscience Unit - University College London
Research on neural computational theories of perception and action, with an emphasis on learning.
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.
GSIC
a group of researchers interested in artificial intelligence, computer supported collaborative learning and grid computing
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.
Institute for Process Control and Robotics - University of Karlsruhe (Germany)
Research on Machine Learning in Robotics, Factory Automation, and Assistance Systems.
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.
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.
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.
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.
Learning Lab at CMU, School of Computer Science
Software systems that learn user preferences, Robot learning, text learning, generic learning methods.
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 - 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.
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