16 citations · 49 across the 15 of their papers we have counts for
9 papers · 1 filter
How to model Human Actions distribution with Event Sequence Data
Egor Surkov, Dmitry Osin, Evgeny Burnaev +1
This paper studies forecasting of the future distribution of events in human action sequences, a task essential in domains like retail, finance, healthcare, and recommendation syst…
Self-Supervised Coarsening of Unstructured Grid with Automatic Differentiation
Sergei Shumilin, Alexander Ryabov, Nikolay Yavich +2
Due to the high computational load of modern numerical simulation, there is a demand for approaches that would reduce the size of discrete problems while keeping the accuracy reaso…
Risk-Averse Reinforcement Learning with Itakura-Saito Loss
Igor Udovichenko, Olivier Croissant, Anita Toleutaeva +2
Risk-averse reinforcement learning finds application in various high-stakes fields. Unlike classical reinforcement learning, which aims to maximize expected returns, risk-averse ag…
GIFT-SW: Gaussian noise Injected Fine-Tuning of Salient Weights for LLMs
Maxim Zhelnin, Viktor Moskvoretskii, Egor Shvetsov +4
Parameter Efficient Fine-Tuning (PEFT) methods have gained popularity and democratized the usage of Large Language Models (LLMs). Recent studies have shown that a small subset of w…
SeqNAS: Neural Architecture Search for Event Sequence Classification
Igor Udovichenko, Egor Shvetsov, Denis Divitsky +6
Neural Architecture Search (NAS) methods are widely used in various industries to obtain high quality taskspecific solutions with minimal human intervention. Event Sequences find w…
Challenges in data-based geospatial modeling for environmental research and practice
Diana Koldasbayeva, Polina Tregubova, Mikhail Gasanov +3
With the rise of electronic data, particularly Earth observation data, data-based geospatial modelling using machine learning (ML) has gained popularity in environmental research.…