no code implementations • 16 Dec 2023 • Daniil Chivilikhin, Artem Pavlenko, Alexander Semenov
If $B$ is an arbitrary subset of the set of variables occurring in a SAT formula $C$, and $A$ is an arbitrary complete SAT solver , then the d-hardness expresses an estimate of the hardness of $C$ w. r. t.
no code implementations • 4 Oct 2022 • Alexander Semenov, Konstantin Chukharev, Egor Tarasov, Daniil Chivilikhin, Viktor Kondratiev
We show that the hardness of SAT encodings for LEC instances can be estimated \textit{w. r. t.}
no code implementations • 8 Jun 2022 • Maksim Borisov, Valeria Kolycheva, Alexander Semenov, Dmitry Grigoriev
We construct a number of visual features measuring complexity of the painting, its points of interest, segmentation-based features, local color features, and features based on Itten and Kandinsky theories, and utilize mixed-effects model to study impact of these features on the painting price.
no code implementations • 28 Apr 2022 • Alexander Semenov, Yixin Zhang, Marisa Ponti
Using data from the annotation activity of citizen scientists in a Swedish marine project, we constructed Deep Neural Network models to predict forthcoming engagement.
no code implementations • 6 Dec 2021 • Alla Kammerdiner, Alexander Semenov, Eduardo Pasiliao
Because the optimization problem is NP-hard, we apply two heuristic procedures, a Greedy algorithm and very large scale neighborhood search, to solve the assignment problem and find the most likely matching of records from multiple datasets into a single entity.
no code implementations • 5 Sep 2020 • Walter Distaso, Rustam Ibragimov, Alexander Semenov, Anton Skrobotov
The paper focuses on econometrically justified robust analysis of the effects of the COVID-19 pandemic on financial markets in different countries across the World.
no code implementations • 17 May 2018 • Alexander Semenov, Ilya Otpuschennikov, Irina Gribanova, Oleg Zaikin, Stepan Kochemazov
We demonstrate the results of applications of Transalg to construction of a number of attacks on various cryptographic functions.
no code implementations • 13 Mar 2018 • Alexander Semenov, Oleg Zaikin, Ilya Otpuschennikov, Stepan Kochemazov, Alexey Ignatiev
Propositional satisfiability (SAT) is at the nucleus of state-of-the-art approaches to a variety of computationally hard problems, one of which is cryptanalysis.
no code implementations • 27 Feb 2017 • Dmitry I. Ignatov, Alexander Semenov, Daria Komissarova, Dmitry V. Gnatyshak
Multimodal clustering is an unsupervised technique for mining interesting patterns in $n$-adic binary relations or $n$-mode networks.
1 code implementation • 4 Jul 2016 • Ilya Otpuschennikov, Alexander Semenov, Irina Gribanova, Oleg Zaikin, Stepan Kochemazov
We implemented this technology in the form of the software system called Transalg, and used it to construct SAT encodings for a number of cryptanalysis problems.
no code implementations • 3 Jul 2015 • Alexander Semenov, Oleg Zaikin
The estimation of effectiveness of the particular partitioning is the value of predictive function in the corresponding point of this space.
no code implementations • 29 Oct 2014 • Stepan Kochemazov, Alexander Semenov
The first problem is to find a disposition of instigators that in several time moments transforms a network from a state where a majority of simple agents are inactive to a state with a majority of active agents.
no code implementations • 7 May 2014 • Ilya Otpuschennikov, Alexander Semenov, Stepan Kochemazov
In this paper we present the Transalg system, designed to produce SAT encodings for discrete functions, written as programs in a specific language.
no code implementations • 4 Aug 2013 • Alexander Semenov, Oleg Zaikin
This paper proposes a method to estimate the total time required to solve SAT in distributed environments via partitioning approach.