12 citations · 34 across the 17 of their papers we have counts for
5 papers · 1 filter
Simplicial SMOTE: Oversampling Solution to the Imbalanced Learning Problem
Oleg Kachan, Andrey Savchenko, Gleb Gusev
SMOTE (Synthetic Minority Oversampling Technique) is the established geometric approach to random oversampling to balance classes in the imbalanced learning problem, followed by ma…
Multimodal Banking Dataset: Understanding Client Needs through Event Sequences
Dzhambulat Mollaev, Alexander Kostin, Maria Postnova +4
Financial organizations collect a huge amount of temporal (sequential) data about clients, which is typically collected from multiple sources (modalities). Despite the urgent pract…
Adversarial Attacks on Deep Models for Financial Transaction Records
Ivan Fursov, Matvey Morozov, Nina Kaploukhaya +7
Machine learning models using transaction records as inputs are popular among financial institutions. The most efficient models use deep-learning architectures similar to those in…
Aggregation of pairwise comparisons with reduction of biases
Nadezhda Bugakova, Valentina Fedorova, Gleb Gusev +1
We study the problem of ranking from crowdsourced pairwise comparisons. Answers to pairwise tasks are known to be affected by the position of items on the screen, however, previous…
Lower Bounds for Multi-armed Bandit with Non-equivalent Multiple Plays
Aleksandr Vorobev, Gleb Gusev
We study the stochastic multi-armed bandit problem with non-equivalent multiple plays where, at each step, an agent chooses not only a set of arms, but also their order, which infl…