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The laboratory carries out research in machine learning (particularly argument based machine learning, inductive logic programming, robot learning), qualitative reasoning with robotics applications, intelligent robotics (planning, learning for planning), machine learning in medicine, and intelligent tutoring systems (ITS for programming and game playing, automated hint generation and the automatic assessment of the level of difficulty of problems for humans).
Research areas:
Machine learning and artificial intelligence
The laboratory carries out research in data mining, machine learning, data visualization, big data analysis and data fusion. We apply computational methods to solve practical problems and focus on systems biology, biomedicine and natural sciences. The laboratory is developing Orange (http://orange.biolab.si), a comprehensive suite that joins machine learning and visual programming, and collaborates in development of cool interactive web-based data exploration platforms like dictyExpress (http://dictyexpress.org).
Research areas:
Computational Biology
Machine learning and artificial intelligence
Our main research topics include development of adaptive algorithms in areas of artificial neural networks, data clustering, data mining, information-theoretic modelling and reinforcement learning, and design of computer systems, ranging from high performance computing to on-chip designs. We are mainly focused on problems where the lack of theoretical knowledge prevents exact solutions and where special software and hardware are demanded for efficient processing. We are also involved in digital logic design of arithmetic circuits, processing on GPUs, and smart wireless sensor networks. More recently, the laboratory is engaged also in experimental research in the field of wireless networks, radio-based localisation and software-defined radio.
Research areas:
Systems and networks
Machine learning and artificial intelligence
The laboratory apursuesresearch in machine learning, neural networks, statistics, image, text and data mining. Recent research has been related to the generation of semi-artificial data, the analysis of big data with the MapReduce approach, evaluating the reliability of single models’ predictions, text summarisation using archetypal analysis, web-user profiling, applying evolutionary computation to data mining, spatial data mining with multi-level directed graphs, bottom-up inductive logic programming, heuristic search methods in clickstream mining, multi-view learning, mining of heterogeneous networks and e-learning.
Research areas:
Machine learning and artificial intelligence
Areas of interest include data acquisition, management, integration, analysis and visualisation, all within the framework of information system development, management and governance. Special interest is devoted to internet of things, big data, real-time data management, the analysis of large networks, data streams, information extraction, etc. We work closely with industry partners in developing and testing new technologies and approaches.
Research areas:
Software engineering and informatics
Machine learning and artificial intelligence
The laboratory is involved in basic and applied research of visually enabled intelligent systems. We have extensive experience with visual object tracking, object detection and categorization, incremental visual learning, as well as with systems for human-robot interactive learning and the development of computer vision solutions for smart mobile devices. Our experience has been accumulated in collaboration with a variety of research partners in a number of the EU, national and industry funded projects which address these research issues.
Research areas:
Machine perception and multimedia
Machine learning and artificial intelligence
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