Research_Groups

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 and 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.
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 - Research on Support Vector Machines, Hidden Markov Models, fusion of generative and discriminative approaches, logical data analysis, large scale data analysis. Martigny, Switzerland.
Institute for Process Control and Robotics - University of Karlsruhe (Germany) - Research on Machine Learning in Robotics, Factory Automation, and Assistance Systems.
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 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.
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 and Natural Language Processing Lab - Freiburg (Germany) - Research on Data Mining, Machine Learning,Inductive Logic Programming, Relational Learning, Machine Learning for Bioinformatics.
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 at the Katholieke Universiteit Leuven - Research in Data mining, Inductive Logic Programming, Learning In Agents.
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.
Machine Learning Group - Stockholm University - Research on inductive logic programming for natural language processing and for knowledge discovery in databases.
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.
Machine Learning Group - University of Waikato - Offers WEKA, an 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 and 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 NeuroCOLT Project - ESPRIT working group on Neural and Computational Learning Theory. Partners, projects, publications archive.
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.