Fall into ML 2024

HSE University invites you to attend annual Fall into ML Conference aimed at students, graduate students and researchers in artificial intelligence. The event is similar to an A* level Conference, which program includes tutorial, panel discussions, workshops on the promising areas of artificial intelligence, series of selected talks and a poster session.

Topics of interest include (but are not limited to): general machine learning, deep learning, reinforcement learning, ML applications (industry, natural sciences, healthcare, neuroscience, social good, climate science, etc.), language models, computer vision, trustworthy machine learning, optimization (convex and non-convex optimization, matrix/tensor methods, etc.), robotics and autonomous vehicles.

Title partner





Conference contents:

Tutorial (RUS)

Modern methods of generative modelling: flow matching and schrödinger bridges
	Alexander Korotin Skoltech Applied AI Center, AIRI

Workshops (RUS/ENG) 

 

Genetic computer, or AI in bioinformatics
	Maria Poptsova HSE University, AI and Digital Science Institute, International Laboratory of Bioinformatics
Science for business: challenges and AI-solutions
	Konstantin Vishnevskiy HSE University, Institute for Statistical Studies and Economics of Knowledge, Centre for Strategic Analysis and Big Data
	Dmitry Zagorulkin  HSE University, Institute for Statistical Studies and Economics of Knowledge, Centre for Strategic Analysis and Big Data
Using AI for intelligent labour market analysis, career guidance and employment forecasting
	Marina Zavertiaeva HSE Campus in Perm, International Laboratory of Intangible-driven Economy
	Pavel Travkin HSE University
Financial AI
	Andrey Savchenko Sber AI Lab

 

 Key talks (RUS/ENG)

Estimating Barycenters of Distributions with Neural Optimal Transport
Alexander Kolesov, Petr Mokrov, Igor Udovichenko, Milena Gazdieva, Gudmund Pammer, Evgeny Burnaev, Alexander Korotin

PV-Tuning: Beyond Straight-Through Estimation for Extreme LLM Compression
Vladimir Malinovskii, Denis Mazur, Ivan Ilin, Denis Kuznedelev, Konstantin Burlachenko, Kai Yi, Dan Alistarh, Peter Richtarik

Towards Robust Full Low-bit Quantization of Super Resolution Networks
Denis Makhov, Irina Zhelavskaya, Ruslan Ostapets, Dehua Song, Kirill Solodskikh 

In-Context Reinforcement Learning for Variable Action Spaces
Viacheslav Sinii, Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Sergey Kolesnikov

Poster Session (RUS/ENG)

Traditionally, on October 26 authors of A*papers in the current year are invited to present their posters during the poster session. Conference board will review applications and selected papers will be invited for an oral presentation. If you are an author of A* paper in 2024 (e.g. CVPR2024, AISTATS2024, ICLR2024, ICML2024 etc) and would like to present a poster at the Conference, please feel free to fill in the form.