Search Results for author: Alexander Semenov

Found 14 papers, 1 papers with code

Decomposing Hard SAT Instances with Metaheuristic Optimization

no code implementations16 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.

Evolutionary Algorithms Metaheuristic Optimization

The influence of color on prices of abstract paintings

no code implementations8 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.

Who will stay? Using Deep Learning to predict engagement of citizen scientists

no code implementations28 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.

Recommendation Systems

Multidimensional Assignment Problem for multipartite entity resolution

no code implementations6 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.

Combinatorial Optimization Entity Resolution

COVID-19: Tail Risk and Predictive Regressions

no code implementations5 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.

Time Series Time Series Analysis

On Cryptographic Attacks Using Backdoors for SAT

no code implementations13 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.

Cryptanalysis

Multimodal Clustering for Community Detection

no code implementations27 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.

Attribute Clustering +1

Encoding Cryptographic Functions to SAT Using Transalg System

1 code implementation4 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.

Cryptanalysis Distributed Computing

Using Monte Carlo method for searching partitionings of hard variants of Boolean satisfiability problem

no code implementations3 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.

Using synchronous Boolean networks to model several phenomena of collective behavior

no code implementations29 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.

Transalg: a Tool for Translating Procedural Descriptions of Discrete Functions to SAT

no code implementations7 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.

Translation

On estimating total time to solve SAT in distributed computing environments: Application to the SAT@home project

no code implementations4 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.

Cryptanalysis Distributed Computing

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