ESPRIT working group on Neural and Computational Learning Theory. Partners, projects, publications archive.

Research on Data Mining, Active Learning and Exploration, Reinforcement Learning for Decision and Control.

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.

Research on Localization and Mapping, Partially Observable Markov Decision Processes, Computer Vision and Image Processing, Robot Architectures and Programming Languages, Learning Algorithms.

Research on computational machine learning tools and theoretical frameworks with applications in computational molecular biology, computer vision, sensory processing, and iterative decoding.

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.

Research on information retrieval and extraction, bioinformatics, connectionist models, hybrid systems.

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...

Research on Neural Networks and Decision Trees.

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.