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September 25, 2026
AI Users Earn Up to 41.8% More Than Non-Users
Research conducted by economists at HSE University has revealed a significant correlation between the regular use of GenAI in the workplace and higher pay among Russian employees. The study found that individuals who frequently use GenAI in their professional activities earn notably more than those who reject these new tools or resort to them occasionally. The salary premium for highly qualified specialists reaches 41.8%. The article was published in the Voprosy Ekonomiki journal.
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Vincent Fardeau, Associate Professor at HSE ICEF, has reached a major career milestone: he recently published his paper ‘Asymmetric Thin Markets’ in the Journal of Financial Economics, successfully passed his major academic review, and received tenure. In this interview, Vincent discusses the story behind the paper, explains the concept of asymmetric thin markets, and shares his advice for young scholars aiming to publish in top-tier journals.
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Supplementary Proceedings of the 4th International Conference on Analysis of Images, Social Networks and Texts (AIST'2015)

Issue 1452. Aachen : CEUR Workshop Proceedings, 2015.
Academic editor: M. Khachay, N. Konstantinova, A. Panchenko, R. Delhibabu, N. Spirin, V. Labunets

This volume contains proceedings of the fourth conference on Analysis of Images, Social Networks and Texts (AIST’2015)1 . The first three conferences in 2012–2014 attracted a significant number of students, researchers, academics and engineers working on interdisciplinary data analysis of images, texts, and social networks. The broad scope of AIST makes it an event where researchers from different domains, such as image and text processing, exploiting various data analysis techniques, can meet and exchange ideas. We strongly believe that this may lead to crossfertilisation of ideas between researchers relying on modern data analysis machinery. Therefore, AIST brings together all kinds of applications of data mining and machine learning techniques. The conference allows specialists from different fields to meet each other, present their work, and discuss both theoretical and practical aspects of their data analysis problems. Another important aim of the conference is to stimulate scientists and people from the industry to benefit from the knowledge exchange and identify possible grounds for fruitful collaboration. The conference was held during April 9–11, 2015. Following an already established tradition, the conference was organised in Yekaterinburg, a cross-roads between European and Asian parts of Russia, the capital of Urals region.The key topics of AIST are analysis of images and videos; natural language processing and computational linguistics; social network analysis; pattern recognition, machine learning and data mining; recommender systems and collaborative technologies; semantic web, ontologies and their applications. The Program Committee and the reviewers of the conference included wellknown experts in data mining and machine learning, natural language processing, image processing, social network analysis, and related areas from leading institutions of 22 countries including Australia, Bangladesh, Belgium, Brazil, Cyprus, Egypt, Finland, France, Germany, Greece, India, Ireland, Italy, Luxembourg, Poland, Qatar, Russia, Spain, The Netherlands, UK, USA and Ukraine.

Chapters
Imitation of Human Behavior in 3D-Shooter Game
Makarov I., Mikhail Tokmakov, Lada Tokmakova, , in: Supplementary Proceedings of the 4th International Conference on Analysis of Images, Social Networks and Texts (AIST'2015)Issue 1452.: Aachen: CEUR Workshop Proceedings, 2015. Ch. 9 P. 64–77.
There are many algorithms for 3D-shooter game artificial intelligence that are based on automatic target recognition with the help of ray casting, scriptbased event systems and many others. In such models game agents have an advantage over human player because computers do not need time for enemy recognition and target aiming processes. The main goal ...
Added: October 9, 2015
Am I Really Happy When I Write “Happy” in My Post?
Porshnev A., Шашкин П. О., , in: Supplementary Proceedings of the 4th International Conference on Analysis of Images, Social Networks and Texts (AIST'2015)Issue 1452.: Aachen: CEUR Workshop Proceedings, 2015. P. 126–136.
Posts published on the Internet could serve as a valuable source of information regarding emotion. Recommendation systems, stock market forecast and other areas are likely to benefit from the advancement in mood classification. To deal with this task, researchers commonly rely on preassembled lexicons of emotional words. In this paper we discuss the possibility of extracting ...
Added: February 18, 2016
Research target: Mathematics Computer Science
Priority areas: IT and mathematics mathematics
Language: English
Full text
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Keywords: сетевой анализанализ изображенийанализ текстовnetwork analysistext miningimage analysis
Supplementary Proceedings of the 4th International Conference on Analysis of Images, Social Networks and Texts (AIST'2015)
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