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Stanislav Kirpichenko, Lev Utkin, Andrei Konstantinov and Vladimir Muliukha
A method for estimating the conditional average treatment effect under the condition of censored time-to-event data, called BENK (the Beran Estimator with Neural Kernels), is proposed. The main idea behind the method is to apply the Beran estimator for e...
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Konstantin Gaipov, Daniil Tausnev, Sergey Khodenkov, Natalya Shepeta, Dmitry Malyshev, Aleksey Popov and Lev Kazakovtsev
Rapid growth in the volume of transmitted information has lead to the emergence of new wireless networking technologies with variable heterogeneous topologies. With limited radio frequency resources, optimal routing problems arise, both at the network de...
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Andrei Konstantinov, Lev Utkin and Vladimir Muliukha
This paper provides new models of the attention-based random forests called LARF (leaf attention-based random forest). The first idea behind the models is to introduce a two-level attention, where one of the levels is the ?leaf? attention, and the attent...
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Lev Eppelbaum and Youri Katz
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Andrei Konstantinov, Lev Utkin and Vladimir Muliukha
A new random forest-based model for solving the Multiple Instance Learning problem under small tabular data, called the Soft Tree Ensemble Multiple Instance Learning, is proposed. A new type of soft decision trees is considered, which is similar to the w...
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Igor Masich, Natalya Rezova, Guzel Shkaberina, Sergei Mironov, Mariya Bartosh and Lev Kazakovtsev
A number of real-world problems of automatic grouping of objects or clustering require a reasonable solution and the possibility of interpreting the result. More specific is the problem of identifying homogeneous subgroups of objects. The number of group...
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Andrei Konstantinov, Stanislav Kirpichenko and Lev Utkin
A new method for estimating the conditional average treatment effect is proposed in this paper. It is called TNW-CATE (the Trainable Nadaraya?Watson regression for CATE) and based on the assumption that the number of controls is rather large and the numb...
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Vladimir Krutikov, Elena Tovbis, Anatoly Bykov, Predrag Stanimirovic, Ekaterina Chernova and Lev Kazakovtsev
We investigate a solution of a convex programming problem with a strongly convex objective function based on the dual approach. A dual optimization problem has constraints on the positivity of variables. We study the methods and properties of transformat...
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Vladimir Stanovov, Lev Kazakovtsev and Eugene Semenkin
Differential evolution (DE) is a popular and efficient heuristic numerical optimization algorithm that has found many applications in various fields. One of the main disadvantages of DE is its sensitivity to parameter values. In this study, we investigat...
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Lev Utkin, Andrey Ageev, Andrei Konstantinov and Vladimir Muliukha
A new modification of the isolation forest called the attention-based isolation forest (ABIForest) is proposed for solving the anomaly detection problem. It incorporates an attention mechanism in the form of Nadaraya?Watson regression into the isolation ...
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