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.
AICML - Alberta Ingenuity Centre for Machine Learning
An internationally recognized node of machine learning researchers at the University of Alberta
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.
Artificial Intelligence Research Laboratory - Iowa State University
Research related to machine learning includes neural networks, automata induction, computational learning theory, data mining, knowledge discovery, bioinformatics.
Automated Learning Group - NASA
Research projects on collective intelligence, surface modeling, autoclass, Bayesian search.
The Auton Project
Research on Data Mining, Active Learning & Exploration, Reinforcement Learning for Decision and Control.
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.
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.
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.
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