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.
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 - 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.
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.
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