Tag "machine learning"

Researchers of the HSE Graduate School of Business trained a machine-learning (ML) model to infer users' subjective wellbeing from social media posts. Having processed 10 million tweets, the researchers compiled a rating of holidays celebrated in Russia based on their popularity. The New Year tops the list, but Russian-speaking users of Twitter are also happy to celebrate Defender of the Fatherland Day, International Women's Day, and Halloween. The study findings have been published in PeerJ Computer Science.

A group of researchers from the HSE Faculty of Computer Science and the Sber AI Lab has increased the speed of gradient boosting, one of the most efficient machine learning algorithms. The proposed approach will make it possible to solve classification and regression problems faster. The results of the work were presented at the NeurIPS conference.

Researchers from HSE University and the Russian Technological University (RTU MIREA) have developed an intelligent system to automate software testing on a variety of platforms. Its computer vision feature is capable of recognising elements in a graphical user interface even after a redesign. The details are published in the Journal of the Siberian Federal University.

A team of researchers from HSE MIEM, LPI RAS, and the University of Southern California have applied machine learning to the analysis of internal defects in perovskite solar cells and proposed ways to improve their energy efficiency. The findings of the study performed on the Cs₂AgBiBr₆ double perovskite can be used to develop more efficient and durable perovskite-based materials. The paper has been published in the Journal of Physical Chemistry Letters.

How can the metaverse help to improve public administration? Can gamification change attitudes to data? And how can governments create ethical data policies? On June 29–30 2022, the International Laboratory for Digital Transformation in Public Administration held an online conference dedicated to these questions and more. The conference was organised and moderated by Laboratory Head Evgeny Styrin and Leading Research Fellow Anna Sanina.

A research team from the HSE University Artificial Intelligence Centre led by Ivan Yamshchikov has developed a model to predict the success of efforts to rehabilitate homeless people. The model can predict the effectiveness of the work of organisations for the homeless with about 80% accuracy. The project was presented at a conference dedicated to the activities of social centres.

HSE scientists Andrey Korotayev and Ilya Medvedev used machine learning (ML) to build an index of instability in the world. The new method made it possible to use a large number of variables and distribute them in non-standard fashion.

Mikhail Guschin, Research Fellow at the HSE University Laboratory of Methods for Big Data Analysis of the Faculty of Computer Science, was appointed coordinator of the machine learning and statistics working group in the LHCb Large Hadron Collider experiment at CERN (the European Organization for Nuclear Research). He will be the only representative of a Russian University among the coordinators for the experiment’s working groups.

A mathematical model of Covid-19 spreading in Nizhny Novgorod Region, which has been created by the Big Data Laboratory at Nizhny Novgorod Development Strategy Project Office, has been widely discussed in the media and on social networks. The research was led by Anastasia Popova, a master’s student of HSE University in Nizhny Novgorod, repeat winner of machine learning competitions, and winner of Ilya Segalovich Award by Yandex. In the following interview given on April 15, Anastasia speaks about how the model was developed, the data it uses, and long-term potential applications.

Researchers have used machine learning to discover that the two most widespread DNA structures — stem-loops and quadruplexes — cause genome mutations that lead to cancer. The results of the study were published in BMC Cancer.