HSE University Opens Joint Laboratory with Samsung Research
© Signature/ iStock
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.
Neural networks and Bayesian models are two popular paradigms in the field of machine learning. The first made a real revolution in the field of processing of big data, giving rise to a new direction, dubbed deep learning. The latter have traditionally been used to process small data. A new mathematical tool, developed in 2010, allows you to design scalable Bayesian models. This makes it possible to apply the mechanisms of Bayesian inference in modern neural networks. Even the first attempts to construct hybrid neuro-Bayesian models lead to unexpected and interesting results. For example, by using Bayesian inference in neural networks, it is possible to compress the network by approximately 100 times without losing the accuracy of its operation. On the other hand, in the very procedure of the approximate Bayesian inference one can also use a neural network to approach the exact a posteriori distribution. Thus, mutual penetration of the two technologies is obtained.
Neuro-Bayesian approach can potentially solve a number of open problems in deep learning: the possibility of a catastrophic over fitting for noised data, the self-confidence of a neural network even in erroneous predictions, uninterpretable decision-making, and vulnerability to adversarial attacks. All these problems are recognized by the scientific community, many teams around the world work on their solution, but there are no ready answers yet.
‘Samsung Electronics is one of the world's technological leaders. In our development we use many models of deep learning. But in order to keep up with competitors, it is not enough just to use ready-made models. We need to create new technologies of machine learning. This is all the more important because the field of deep learning has not yet "settled" and every year there are new models, and existing ones quickly become obsolete,’ explains (Geunbae Lee, the Head of the AI Center, Samsung Research). ‘All this means that humanity has not yet found the optimal solution for processing big data. Therefore, cooperation with leading scientific groups in the field of machine learning and artificial intelligence in universities around the world allows us to "keep our finger on the pulse" and keep track of the latest achievements in the field, as well as get exclusive access to technologies created in partner laboratories.’
‘Samsung's decision to choose our group as a key partner in Russia, giving us the opportunity to focus exclusively on basic research, is a sign of recognition of our scientific achievements and at the same time a credit of confidence that we will try to fully justify,’ says the head of the joint laboratory and the head of the Bayesian methods research group, Dmitry Vetrov. ‘Usually large companies try to use scientists to solve specific applied problems. I am glad that our Korean partner understands the importance of research on the development of new technologies, rather than solving specific problems. Our laboratory will deal with the creation of new technologies, that is, the most interesting from the point of view of the scientist. Our goals completely coincide with the wishes of our partners, which serves as a guarantee of successful and long-term cooperation.’
In addition to scientific projects, the HSE-Samsung joint laboratory will actively participate in educational activities. Students and post-graduate students of the Faculty of Computer Science will be attracted to work in it. In August 2018, with the support of Samsung, the second summer school on neuro-Bayesian methods will be held. This time it will be conducted in English and several leading scientists will take part in it. The registration is still open for the summer school.
See also:
‘We Bring Together the Best Russian Scientists and AI Researchers at HSE University Site’
On October 25–26, 2024, HSE University’s AI and Digital Science Institute and the AI Research Centre hold the Fall into ML 2024 conference in Moscow. This year’s event will focus on the prospects in development of fundamental artificial intelligence, with SBER as its conference title partner.
HSE Researchers Demonstrate Effectiveness of Machine Learning in Forecasting Inflation
Inflation is a key indicator of economic stability, and being able to accurately forecast its levels across regions is crucial for governments, businesses, and households. Tatiana Bukina and Dmitry Kashin at HSE Campus in Perm have found that machine learning techniques outperform traditional econometric models in long-term inflation forecasting. The results of the study focused on several regions in the Privolzhskiy Federal District have been published in HSE Economic Journal.
‘The Goal of the Spring into ML School Is to Unite Young Scientists Engaged in Mathematics of AI’
The AI and Digital Science Institute at the HSE Faculty of Computer Science and Innopolis University organised a week-long programme for students, doctoral students, and young scientists on the application of mathematics in machine learning and artificial intelligence. Fifty participants of Spring into ML attended 24 lectures on machine learning, took part in specific pitch sessions, and completed two mini-courses on diffusion models—a developing area of AI for data generation.
Software for Rapid Detection of Dyslexia Developed in Russia
HSE scientists have developed a software tool for assessing the presence and degree of dyslexia in school students based on their gender, age, school grade, and eye-tracking data. The application is expected to be introduced into clinical practice in 2024. The underlying studies were conducted by specialists in machine learning and neurolinguistics at the HSE AI Research Centre.
‘Every Article on NeurIPS Is Considered a Significant Result’
Staff members of the HSE Faculty of Computer Science will present 12 of their works at the 37th Conference and Workshop on Neural Information Processing Systems (NeurIPS), one of the most significant events in the field of artificial intelligence and machine learning. This year it will be held on December 10–16 in New Orleans (USA).
HSE University Holds HSE Sber ML Hack
On November 17-19, The HSE Faculty of Computer Science, SBER and cloud technology provider Cloud.ru organised HSE Sber ML Hack, a hackathon based around machine learning. More than 350 undergraduate and graduate students from 54 leading Russian universities took part in the competition.
HSE University Hosts Fall into ML 2023 Conference on Machine Learning
Over three days, more than 300 conference participants attended workshops, seminars, sections and a poster session. During panel discussions, experts deliberated on the regulation of artificial intelligence (AI) technologies and considered collaborative initiatives between academic institutions and industry to advance AI development through megaprojects.
HSE University to Host ‘Fall into ML 2023’ Machine Learning Conference
Machine Learning (ML) is a field of AI that examines methods and algorithms that enable computers to learn based on experience and data and without explicit programming. With its help, AI can analyse data, recall information, build forecasts, and give recommendations. Machine learning algorithms have applications in medicine, stock trading, robotics, drone control and other fields.
New Labs to Open at Faculty of Computer Science
Based on the results of a project competition, two new laboratories are opening at HSE University’s Faculty of Computer Science. The Laboratory for Matrix and Tensor Methods in Machine Learning will be headed by Maxim Rakhuba, Associate Professor at the Big Data and Information Retrieval School. The Laboratory for Cloud and Mobile Technologies will be headed by Dmitry Alexandrov, Professor at the School of Software Engineering.
Joint Project of Scientists from HSE University and Surgut State University to Help Prevent Recurrent Heart Attacks and Strokes
One of the winning projects of a competition held by HSE University’s Mirror Laboratories last June focuses on the use of machine learning technologies to predict the outcomes of acute coronary syndrome. It is implemented by HSE University’s International Laboratory of Bioinformatics together with the Research and Educational Centre of the Medical Institute at Surgut State University. Maria Poptsova, Head of the International Laboratory of Bioinformatics and Associate Professor at HSE University’s Faculty of Computer Science, talks about how this joint project originated, how it will help patients, and how work to implement it will be organised.