103 citations · 171 across the 14 of their papers we have counts for
8 papers · 1 filter
Detecting Video Game Player Burnout with the Use of Sensor Data and Machine Learning
Anton Smerdov, Andrey Somov, Evgeny Burnaev +2
Current research in eSports lacks the tools for proper game practising and performance analytics. The majority of prior work relied only on in-game data for advising the players on…
Towards forecast techniques for business analysts of large commercial data sets using matrix factorization methods
Rodrigo Rivera-Castro, Ivan Nazarov, Evgeny Burnaev
This research article suggests that there are significant benefits in exposing demand planners to forecasting methods using matrix completion techniques. This study aims to contrib…
Topology-based Clusterwise Regression for User Segmentation and Demand Forecasting
Rodrigo Rivera-Castro, Aleksandr Pletnev, Polina Pilyugina +4
Topological Data Analysis (TDA) is a recent approach to analyze data sets from the perspective of their topological structure. Its use for time series data has been limited. In thi…
Topological Data Analysis for Portfolio Management of Cryptocurrencies
Rodrigo Rivera-Castro, Polina Pilyugina, Evgeny Burnaev
Portfolio management is essential for any investment decision. Yet, traditional methods in the literature are ill-suited for the characteristics and dynamics of cryptocurrencies. T…
An industry case of large-scale demand forecasting of hierarchical components
Rodrigo Rivera-Castro, Ivan Nazarov, Yuke Xiang +3
Demand forecasting of hierarchical components is essential in manufacturing. However, its discussion in the machine-learning literature has been limited, and judgemental forecasts…
Differentiable Language Model Adversarial Attacks on Categorical Sequence Classifiers
I. Fursov, A. Zaytsev, N. Kluchnikov +2
An adversarial attack paradigm explores various scenarios for the vulnerability of deep learning models: minor changes of the input can force a model failure. Most of the state of…