13 citations · 29 across the 4 of their papers we have counts for
4 papers
Machine Learning-Driven Compensation for Non-Ideal Channels in AWG-Based FBG Interrogator
Ivan A. Kazakov, Iana V. Kulichenko, Egor E. Kovalev +5
We present an experimental study of a fiber Bragg grating (FBG) interrogator based on a silicon oxynitride (SiON) photonic integrated arrayed waveguide grating (AWG). While AWG-bas…
Scalable Cross-Entropy Loss for Sequential Recommendations with Large Item Catalogs
Gleb Mezentsev, Danil Gusak, Ivan Oseledets +1
Scalability issue plays a crucial role in productionizing modern recommender systems. Even lightweight architectures may suffer from high computational overload due to intermediate…
RECE: Reduced Cross-Entropy Loss for Large-Catalogue Sequential Recommenders
Danil Gusak, Gleb Mezentsev, Ivan Oseledets +1
Scalability is a major challenge in modern recommender systems. In sequential recommendations, full Cross-Entropy (CE) loss achieves state-of-the-art recommendation quality but con…
Eco2AI: carbon emissions tracking of machine learning models as the first step towards sustainable AI
Semen Budennyy, Vladimir Lazarev, Nikita Zakharenko +9
The size and complexity of deep neural networks continue to grow exponentially, significantly increasing energy consumption for training and inference by these models. We introduce…