102 citations · 215 across the 26 of their papers we have counts for
6 papers · 1 filter
Long-term hail risk assessment with deep neural networks
Ivan Lukyanenko, Mikhail Mozikov, Yury Maximov +1
Hail risk assessment is necessary to estimate and reduce damage to crops, orchards, and infrastructure. Also, it helps to estimate and reduce consequent losses for businesses and,…
Ranking-Based Physics-Informed Line Failure Detection in Power Grids
Aleksandra Burashnikova, Wenting Li, Massih Amini +2
Climate change increases the number of extreme weather events (wind and snowstorms, heavy rains, wildfires) that compromise power system reliability and lead to multiple equipment…
Data-Driven Chance Constrained AC-OPF using Hybrid Sparse Gaussian Processes
Mile Mitrovic, Aleksandr Lukashevich, Petr Vorobev +3
The alternating current (AC) chance-constrained optimal power flow (CC-OPF) problem addresses the economic efficiency of electricity generation and delivery under generation uncert…
Data-Driven Stochastic AC-OPF using Gaussian Processes
Mile Mitrovic, Aleksandr Lukashevich, Petr Vorobev +4
In recent years, electricity generation has been responsible for more than a quarter of the greenhouse gas emissions in the US. Integrating a significant amount of renewables into…
Learning over No-Preferred and Preferred Sequence of Items for Robust Recommendation (Extended Abstract)
Aleksandra Burashnikova, Yury Maximov, Marianne Clausel +3
This paper is an extended version of [Burashnikova et al., 2021, arXiv: 2012.06910], where we proposed a theoretically supported sequential strategy for training a large-scale Reco…
Self-Training: A Survey
Massih-Reza Amini, Vasilii Feofanov, Loic Pauletto +3
Semi-supervised algorithms aim to learn prediction functions from a small set of labeled observations and a large set of unlabeled observations. Because this framework is relevant…