4 citations · 5 across the 18 of their papers we have counts for
3 papers · 1 filter
Memory-efficient particle filter recurrent neural network for object localization
Roman Korkin, Ivan Oseledets, Aleksandr Katrutsa
This study proposes a novel memory-efficient recurrent neural network (RNN) architecture specified to solve the object localization problem. This problem is to recover the object s…
Multiparticle Kalman filter for object localization in symmetric environments
Roman Korkin, Ivan Oseledets, Aleksandr Katrutsa
This study considers the object localization problem and proposes a novel multiparticle Kalman filter to solve it in complex and symmetric environments. Two well-known classes of f…
Federated Privacy-preserving Collaborative Filtering for On-Device Next App Prediction
Albert Sayapin, Gleb Balitskiy, Daniel Bershatsky +5
In this study, we propose a novel SeqMF model to solve the problem of predicting the next app launch during mobile device usage. Although this problem can be represented as a class…