EN

Tag "machine learning"

HSE Researcher Appointed Coordinator in Large Hadron Collider Experiment

HSE Researcher Appointed Coordinator in Large Hadron Collider Experiment
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.

‘Data Mining Can Help Forecast the Pandemic Situation with an Accuracy Within 2.5%’

Anastasia Popova
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.

DNA Secondary Structures Lead to Gene Mutations that Increase the Risk of Cancer

DNA Secondary Structures Lead to Gene Mutations that Increase the Risk of Cancer
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.

HSE Opens Laboratory of Financial Data Analysis

HSE Opens Laboratory of Financial Data Analysis
Part of the Centre of Deep Learning and Bayesian Methods and another partner project between Sberbank and HSE University’s Faculty of Computer Science, the laboratory will focus on applying machine learning methods to financial services.

HSE Professor to Head Up Machine Learning Research at Samsung Centre for Artificial Intelligence

Dmitry Vetrov, Professor of the HSE Faculty of Computer Science
On May 29, Samsung opened its new Artificial Intelligence Centre in Moscow. Dmitry Vetrov, Professor of the HSE Faculty of Computer Science, will become one of its leaders and oversee research in machine learning.

Machine Learning Helping to Save Money at CERN

Machine Learning Helping to Save Money at CERN
Researchers at HSE’s Laboratory of Methods for Big Data Analysis (LAMBDA) and the Yandex School of Data Analysis have significantly reduced the cost of CERN’s future SHiP detector. The detector will search for particles responsible for still unexplained phenomena in the Universe. With use of modern machine learning methods, LAMBDA and Yandex scientists came up with very effective configuration of magnets which protect the detector from background particles. As a result, the cost of the entire structure was reduced by 25%.

HSE University Opens Joint Laboratory with Samsung Research

Samsung-HSE Laboratory will develop mechanisms of Bayesian inference in modern neural networks, which will solve a number of problems in deep learning. The laboratory team will be made up of the members of the Bayesian Methods Research Group — one of the strongest scientific groups in Russia in the field of machine learning and Bayesian inference. It will be headed by a professor of the Higher School of Economics Dmitry Vetrov.

How to Adjust a Smaller Size Neural Network without Quality Loss

Staff members of the HSE Faculty of Computer Science recently presented their papers at the biggest international conference on machine learning, Neural Information Processing Systems (NIPS)’.

Faculty of Computer Science Staff Attend International Conference on Machine Learning

Faculty of Computer Science Staff Attend International Conference on Machine Learning
On August 6-11 the 34th International Conference on Machine Learning was held in Sydney, Australia. This conference is ranked A* by CORE, and is one of two leading conferences in the field of machine learning. It has been held annually since 2000, and this year, more than 1,000 participants from different countries took part.