80 citations · 119 across the 5 of their papers we have counts for
6 papers
Automated Evolutionary Optimization for Resource-Efficient Neural Network Training
Ilia Revin, Leon Strelkov, Vadim A. Potemkin +2
There are many critical challenges in optimizing neural network models, including distributed computing, compression techniques, and efficient training, regardless of their applica…
Integration Of Evolutionary Automated Machine Learning With Structural Sensitivity Analysis For Composite Pipelines
Nikolay O. Nikitin, Maiia Pinchuk, Valerii Pokrovskii +7
Automated machine learning (AutoML) systems propose an end-to-end solution to a given machine learning problem, creating either fixed or flexible pipelines. Fixed pipelines are tas…
Composite model of seismic monitoring data analysis during mining operations on the example of the Kukisvumchorrskoye deposit of JSC Apatit
Ilia Revin
Geomechanical monitoring of a rock massif is an actively developing branch of geomechanics. It is almost impossible to single out a methodology and approaches for data collection a…
Automated Evolutionary Approach for the Design of Composite Machine Learning Pipelines
Nikolay O. Nikitin, Pavel Vychuzhanin, Mikhail Sarafanov +6
The effectiveness of the machine learning methods for real-world tasks depends on the proper structure of the modeling pipeline. The proposed approach is aimed to automate the desi…
Hybrid and Automated Machine Learning Approaches for Oil Fields Development: the Case Study of Volve Field, North Sea
Nikolay O. Nikitin, Ilia Revin, Alexander Hvatov +2
The paper describes the usage of intelligent approaches for field development tasks that may assist a decision-making process. We focused on the problem of wells location optimizat…
Multi-Objective Evolutionary Design of Composite Data-Driven Models
Iana S. Polonskaia, Nikolay O. Nikitin, Ilia Revin +2
In this paper, a multi-objective approach for the design of composite data-driven mathematical models is proposed. It allows automating the identification of graph-based heterogene…