| 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. |
| 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. |
| 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. |