Artificial Intelligence: Machine Learning: Research Groups: Page 2

Research on Neural Networks and Decision Trees.

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

Research on symbolic and numerical approaches to machine learning, first order logic, intelligent document processing, spatial data mining, human-computer interaction.

Research on inductive logic programming for natural language processing and for knowledge discovery in databases.

Research on machine learning theory, kernel methods for text analysis, support vector machines, kernel theory.

Large group with projects in robot learning, data mining for manufacturing and in multimedia databases, causal inference, and disclosure limitation.

Research in Data mining, Inductive Logic Programming, Learning In Agents.

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.

Research projects mainly focused on text: Intelligent Information Access, Text Summarization, Text Analysis for Knowledge Acquisition.

Applied research in data mining, knowledge discovery, pattern recognition, and automated classification and clustering.

Research projects on collective intelligence, surface modeling, autoclass, Bayesian search.

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.

Analysis of functional genomics data, Construction of data-dependent metrics for focusing data analysis on relevant or important aspects of the data.

An on-line handwriting recognition engine based upon statistical dynamic time warping (SDTW) and support vector machines with a Gaussian DTW kernel (SVM-GDTW).

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.

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.