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Regular version of the site

Associate Professor of School of Data Analysis and Artificial Intelligence, Dmitry Ignatov, organized international workshop EEML 2017

The Fourth International Workshop on Experimental Economics and Machine Learning (EEML 2017) took place from September 17 till 18 at Technical University of Dresden. The international team of workshop organisers includes Prof. Andreas Hilbert (Faculty of Economics, TUD), Kai Heinrich (PhD, Faculty of Economics, TUD), Rustam Tagiew  (PhD, Ontonovation),  Radhakrishnan Delhibabu (PhD, Kazan Federal University) and associate professor of Data Analaysis and Artificial Intelligence Department of CS Faculty, Dmitry Ignatov.



In general, this workshop is devoted to modern data analysis techniques for understanding economical behaviour of people and organisations. In particular, for example, based  on  experimental data, deviations of individuals' behaviour from theoretical equlibria are studied by means of machine learning techniques. Data Mining and Machine Learning are discussed as tools for Econometrics

Fig. 2 Kai Heinrich is talking on the role of Data Science for Economics

Anna Muratova, alumni of HSE's master program on Data Science and a team member of the research group on  demographic sequence mining, gave a talk on machine learning approaches, such as Support Vector Machines with customised kernels and  Reccurrent Neural Networks for sequence classification. Mikhail Kamenschikov (avito.ru) gave a talk on their solution for  the ACM RecSys Challenge 2017 in co-authorship with PhD student of the department, Vasily Rubtsov, and others.

A combined talk of  R. Tagiew and D. Ignatov  was devoted to data analysis of scientific publication behaviour in Computer Science by means of DBLP data.

Fig 3 A talk by Rustam Tagiew

And Scopus indexed workshop proceedings' volume is to appear soon.