15 citations · 19 across the 12 of their papers we have counts for
4 papers · 1 filter
EBES: Easy Benchmarking for Event Sequences
Dmitry Osin, Igor Udovichenko, Viktor Moskvoretskii +2
Event Sequences (EvS) refer to sequential data characterized by irregular sampling intervals and a mix of categorical and numerical features. Accurate classification of these seque…
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…
MLEM: Generative and Contrastive Learning as Distinct Modalities for Event Sequences
Viktor Moskvoretskii, Dmitry Osin, Egor Shvetsov +5
This study explores the application of self-supervised learning techniques for event sequences. It is a key modality in various applications such as banking, e-commerce, and health…