Заједнички састанак Одељења за математику и Семинара за рачунарство и примењену математику биће одржан у петак, 1. септембра 2017. у сали 301ф Математичког института САНУ са почетком у 14 часова.
Предавач: Зоран Обрадовић, L.H. Carnell Professor of Data Analytics Temple University, Philadelphia, USA
Наслов предавања: STRUCTURED REGRESSION IN LARGE TEMPORAL NETWORKS
Апстракт: In the first part of this talk we will present a novel sampling-based structured regression method for prediction on top of temporal networks. The algorithm allows efficient learning of an ensemble model by automatically skipping the entire re-training or some phases of the training process in an evolving environment. In conducted experiments the new method was about 140 time faster than alternative structured regression approaches while it was also more accurate as evident on modeling the H3N2 Virus Influenza network. The second part of the talk will describe an efficient algorithm to uncover the underlying dependency structure in high dimensional data. This is achieved by relaying on Cholesky decomposition to learn a sparse Gaussian Markov Random Field. The new method is applied to discover the connectivity structure among gene expressions in septic patients.
Results reported in this talk are published at:
• Pavlovski, M., Zhou, F., Stojković, I., Kočarev, Lj., Obradović, Z. “Adaptive Skip-Train Structured Regression for Temporal Networks,” Proc. European Conf. Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), Sept. 2017.
• Stojković, I., Jelisavčić, V., Milutinović, V., Obradović, Z. “Fast Sparse Gaussian Markov Random Fields Learning Based on Cholesky Factorization,” Proc. 26th Int’l Joint Conf. Artificial Intelligence (IJCAI), Aug. 2017.
Биографија предавача: Zoran Obradović is an Academician at the Academia Europaea (the Academy of Europe) and a Foreign Academician at the Serbian Academy of Sciences and Arts. He is a L.H. Carnell Professor of Data Analytics at Temple University, Professor in the Department of Computer and Information Sciences with a secondary appointment in Department of Statistical Science, and is the Director of the Center for Data Analytics and Biomedical Informatics. His research interests include data science and complex networks in decision support systems. He is the executive editor at the journal on Statistical Analysis and Data Mining and is an editorial board member at eleven journals. He is the program co-chair for the IEEE Big Data 2017 conference and was co-chair for 2013 and 2014 SIAM International Conference on Data Mining and was the program or track chair at many data mining and biomedical informatics conferences. He also served as the chair at the SIAM Activity Group on Data Mining and Analytics for 2014 and 2015 years, He has published more than 350 articles and is cited more than 19,500 times (H-index 52). For more details see http://www.dabi.temple.edu/~