Research Groups

Research Groups Links

• 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 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.
  
• Center for Automated Learning and Discovery - CMU Large group with projects in robot learning, data mining for manifacturing and in multimedia databases, causal inference, disclosure limitation, World Wide Web.
  
• Centre for Learning Systems and Applications (LSA) - University of Kaiserslautern (Germany) Research on Machine Learning, Case-based Reasoning, Knowledge Acquisition
  
• 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.
  
• Gatsby Computational Neuroscience Unit - University College London Research on neural computational theories of perception and action, with an emphasis on learning.
  
• 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.
  
• 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.
  
• 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.
  
• 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 Group - Stockholm University Research on inductive logic programming for natural language processing and for knowledge discovery in databases.
  
• Computational Intelligence Group - University of Bristol Research on kernel methods, support vector machines, neural networks, machine vision, bioinformatics, computational learning theory.
  
• The Machine Learning Systems Group at JPL Applied research in data mining, knowledge discovery, pattern recognition, and automated classification and clustering.
  
• Machine Learning Research Group of Rutgers University Research interest in online algorithms, sequence categorization, action prediction, genetic algorithms, and feature generation/selection.
  
• 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.
  
• Machine Learning Research Group - UW-Madison Research on information retrieval and extraction, bioinformatics, connectionist models, hybrid systems.
  
• 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.
  
• Institute for Process Control and Robotics - University of Karlsruhe (Germany) Research on Machine Learning in Robotics, Factory Automation, and Assistance Systems.
  
• 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.
  
• Complexity of Learning - Royal Halloway University of London Resarch on machine learning theory, kernel methods for text analysis, support vector machines, kernel theory.
  
• 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.
  
• Machine Learning Group - University of York Research mainly devoted to inductive logic programming. Applications include drug design, protein shape prediction and satellite fault diagnosis.
  
• 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.
  
• 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 and Natural Language Processing Lab - Freiburg (Germany) Research on Data Mining, Machine Learning,Inductive Logic Programming, Relational Learning, Machine Learning for Bioinformatics.
  
• 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 Group - University of Waikato Offers WEKA, a comprehensive, open-source (GPL) machine learning / data mining toolkit in Java. Classification, regression, clustering, association rules and more. Command-line and GUI interfaces.
  
• 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.
  
• 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.
  
• 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 Laboratory - UMass Research on Neural Networks and Decision Trees.
  
• Machine Learning at the Katholieke Universiteit Leuven Research in Data mining, Inductive Logic Programming, Learning In Agents.
  
• The Auton Project Research on Data Mining, Active Learning & Exploration, Reinforcement Learning for Decision and Control.
  
• Machine Learning Group, University of Sydney Research on First-order learning (also known as inductive logic programming), Learning to predict values (also known as regression), Hybrid classification methods, Construction of new features that simplify theories, Learning theory, especially aspects of the Minimum Description Length principle.
  
• Automated Learning Group - NASA Research projects on collective intelligence, surface modeling, autoclass, Bayesian search.
  
• 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.
  
• 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.
  
• 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.
  
• Learning Lab at CMU, School of Computer Science Software systems that learn user preferences, Robot learning, text learning, generic learning methods.
  
• AI Unit - University of Dortmund (Germany) Research on representation and acquisition of knowledge in the subareas machine learning and text, knowledge discovery in databases, learning and cognitive science, and learning robots.
  
• 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.