In January 2016, Yahoo announce the public release of the largest-ever machine learning data set to the international research community. The data set stands at a massive ~110B events (13.5TB uncompressed) of anonymized user-news item interaction data, collected by recording the user-news item interactions of about 20M users from February 2015 to May 2015. see: […]
Author Archive for: Andreas Holzinger
About Andreas Holzinger
Andreas and his Group work consistently on a synergistic combination of methodologies and approaches of two areas that offer ideal conditions towards unraveling problems in sensemaking of high-dimensional, complex data sets: Human-Computer Interaction (HCI) and Knowledge Discovery/Data Mining (KDD), with the goal of supporting human intelligence with machine learning – human-in-the-loop – to discover new, previously unknown insights into the data.
Entries by Andreas Holzinger
Mastering the game of Go with deep neural networks and tree search – a very recent paper in Nature: Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., Van Den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., Dieleman, S., Grewe, D., Nham, J., Kalchbrenner, N., Sutskever, I., Lillicrap, T., Leach, […]
Date: Tuesday, 26th January 2016, Start: 10:00, End: 17:00; Venue: Graz University of Technology, Institute of Computer Graphics and Knowledge Visualization CGV, hosted by Prof. Tobias SCHRECK Address: Inffeldgasse 16c, A-8010 Graz <maps and directions> Machine learning is the most growing field in computer science [Jordan, M. I. & Mitchell, T. M. 2015. Machine learning: […]
We wish you a prosperous scientific 2016 with a lot of crazy ideas and successful breakthrough discoveries !
Again machine learning made it to the title page of Science: A nice further proof for the importance of the human-in-the-loop by a paper of Lake, B. M., Salakhutdinov, R. & Tenenbaum, J. B. 2015. Human-level concept learning through probabilistic program induction. Science, 350, (6266), 1332-1338. Whilst humans can learn new concepts often from a […]
Workshop Machine Learning for Health Informatics Machine learning is a large and rapidly developing subfield of computer science that evolved from artificial intelligence (AI) and is tightly connected with data mining and knowledge discovery. The ultimate goal of machine learning is to design and develop algorithms which can learn from data. Consequently, machine learning systems […]
Title: Coordination of post-translational modifications in human protein interaction network Lecturer: Ulrich Stelzl, Network Pharmacology, Insitute of Pharmaceutical Sciences, Karl-Franzens University Graz Abstract: Comprehensive protein interaction networks are prerequisite for a better understanding of complex genotype to phenotype relationships. Post – translational modifications (PTMs) regulate protein activity, stability and protein interaction (PPI) profiles critical for […]
We welcome Irina KUZNETSOVA to our group, who will do her PhD with us on the topic of machine learning for mitochondria research Her inauguratioal talk is on Mitochondrial Interactions Mitochondrial diseases are progressive and debilitating multi-system disorders that occur at a frequency of up to 1 in 5,000 live births with no known cure. […]
The potential of metabolomics and its various data types Lecturer: Natalie BORDAG, CBmed – Center for Biomarker Research in Medicine Graz Abstract: Metabolomics is one of the youngest -omics technologies primarily concerned with the identification and quantification of small molecules (<1500 Da). The specific advantage of metabolomics in biomarker research lies in the concept, that […]
Visual-Interactive Search and Exploration in Complex Data Repositories – Feature-Based Search, Applications and Research Challenges Lecturer: Tobias SCHRECK, University of Konstanz and Graz University of Technology <link> Abstract: Advances in data acquisition and storage technology are leading to the creation of large, complex data sets in many different domains including science, engineering or social media. […]