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arXiv 2023年

作者： Pasechniuk, Dmitrii A. Lobanov, Aleksandr Gasnikov, Alexander Mohamed bin Zayed University of Artificial Intelligence United Arab Emirates Moscow Institute of Physics and Technology Dolgoprudny Russia Kharkevich Institute for Information Transmission Problems RAS Russia Ivannikov Institute for System Programming RAS Russia Skoltech Russia

MSC Codes 65K10In this paper, we leverage an information-theoretic upper bound on the maximum admissible level of noise (MALN) in convex Lipschitz-continuous zeroth-order optimisation to establish corresponding upper bounds for classes of strongly convex and smooth problems. We derive these bounds through non-constructive proofs via optimal reductions. Furthermore, we demonstrate that by employing a one-dimensional grid-search algorithm, one can devise an algorithm for simplex-constrained optimisation that offers a superior upper bound on the MALN compared to the case of ball-constrained optimisation and estimates asymptotic in dimensionality. © 2023, CC BY.

关键词： Constrained optimization

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Docmarking: Real-Time Screen-Cam Robust Document Image Watermarking

arXiv

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arXiv 2023年

作者： Yakushev, Aleksey Markin, Yury Obydenkov, Dmitry Frolov, Alexander Fomin, Stas Akopyan, Manuk Kozachok, Alexander Gaynov, Arthur Ivannikov Institute for System Programming of the RAS Russia Russian Federation Security Guard Service Federal Academy Russia Ministry of Defence The Russian Federation Moscow Russia

This paper focuses on investigation of confidential documents leaks in the form of screen photographs. Proposed approach does not try to prevent leak in the first place but rather aims to determine source of the leak. Method works by applying on the screen a unique identifying watermark as semi-transparent image that is almost imperceptible for human eyes. Watermark image is static and stays on the screen all the time thus watermark present on every captured photograph of the screen. The key components of the approach are three neural networks. The first network generates an image with embedded message in a way that this image is almost invisible when displayed on the screen. The other two neural networks are used to retrieve embedded message with high accuracy. Developed method was comprehensively tested on different screen and cameras. Test results showed high efficiency of the proposed approach. © 2023, CC BY-NC-ND.

关键词： Image watermarking

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High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise 41

High-Probability Convergence for Composite and Distributed S...

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41st International Conference on Machine Learning, ICML 2024

作者： Gorbunov, Eduard Sadiev, Abdurakhmon Danilova, Marina Horváth, Samuel Gidel, Gauthier Dvurechensky, Pavel Gasnikov, Alexander Richtárik, Peter Mohamed bin Zayed University of Artificial Intelligence United Arab Emirates King Abdullah University of Science and Technology Saudi Arabia Moscow Institute of Physics and Technology Russia Université de Montréal Mila Canada Canada CIFAR AI Canada Weierstrass Institute for Applied Analysis and Stochastics Germany University Innopolis Russia Ivannikov Institute for System Programming RAS Russia Skolkovo Institute of Science and Technology Russia

High-probability analysis of stochastic first-order optimization methods under mild assumptions on the noise has been gaining a lot of attention in recent years. Typically, gradient clipping is one of the key algorithmic ingredients to derive good high-probability guarantees when the noise is heavy-tailed. However, if implemented naïvely, clipping can spoil the convergence of the popular methods for composite and distributed optimization (Prox-SGD/Parallel SGD) even in the absence of any noise. Due to this reason, many works on high-probability analysis consider only unconstrained non-distributed problems, and the existing results for composite/distributed problems do not include some important special cases (like strongly convex problems) and are not optimal. To address this issue, we propose new stochastic methods for composite and distributed optimization based on the clipping of stochastic gradient differences and prove tight high-probability convergence results (including nearly optimal ones) for the new methods. In addition, we also develop new methods for composite and distributed variational inequalities and analyze the high-probability convergence of these methods. Copyright 2024 by the author(s)

关键词： Stochastic systems

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Checking Robustness of Web Services based on Solving Automata Equations

Checking Robustness of Web Services based on Solving Automat...

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Annual Siberian Russian Workshop on Electron Devices and Materials (EDM)

作者： Anton Kolomeets Ekaterina Shirokova Maxim Gromov Nina Yevtushenko MainConcept-NLD LLC Tomsk Russia Tomsk State University Tomsk Russia Ivannikov Institute for System Programming of RAS Higher School of Economics Moscow Russia

In this paper, we consider checking the robustness of web services using the model of finite state automata and analyzing the solvability of an automaton equation over the concatenation operator. The paper contains the procedure for constructing the largest solution for a solvable automata equation, since a solution to the equation describes a malicious input. Experimental results have shown that this approach can be effective when checking the robustness of web services.

关键词： Analytical models Web services Conferences Automata Robustness Mathematical model Electron devices

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Profile-based type reconstruction for decompilation

IEEE International Conference on Program Comprehension

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IEEE International Conference on Program Comprehension 2009年 263-267页

作者： Troshina, K. Chernov, A. Fokin, A. Institute for System Programming RAS 25 Alexander Solzhenitsyn st. Moscow 109004 Russia Moscow State University Computational Math. and Cybernetics Dept. Leninskie Gory Moscow Russia

ISBN: (纸本)9781424439973

Decompilation is reconstruction of a program in a highlevel language from a program in a low-level language. In most cases static decompilation is unable to completely reconstruct high-level data types due to loss of typing information during compilation. We present several profilebased techniques that help to recover high-level types. The techniques include pointer/integer determination by value profiling and composite type identification by heap profiling. © 2009 IEEE.

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Test Program Generator MicroTESK for RISC-V

Test Program Generator MicroTESK for RISC-V

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International Workshop on Microprocessor Test and Verification (MTV)

作者： Mikhail Chupilko Alexander Kamkin Artem Kotsynyak Alexander Protsenko Sergey Smolov Andrei Tatarnikov Ivannikov Institute for System Programming of the Russian Academy of Sciences (ISP RAS) Lomonosov Moscow State University (MSU) National Research University - Higher School of Economics (HSE)

ISBN: (纸本)9781538692516

The paper presents a test program generator for functional verification of RISC-V microprocessors. The generator is implemented on the base of MicroTESK framework and consists of formal specifications of RISC-V ISA and ISA-independent core. The specifications describe instructions' syntax and semantics and can be easily modified to support more instructions (including custom extensions). The core implements techniques of instruction sequences composition and test data generation. Test programs are generated from test templates, describing the programs' structural and behavioral properties; among generation techniques, random, combinatorial, and constraint-based ones are supported.

关键词： Registers Microprocessors Object oriented modeling Generators Syntactics Standards Computer architecture

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Nesterov’s method of dichotomy via Order Oracle: The problem of optimizing a two-variable function on a square

arXiv

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arXiv 2024年

作者： Chervonenkis, Boris Krasnov, Andrei Gasnikov, Alexander Lobanov, Aleksandr Moscow Institute of Physics and Technology Russia Institute for Information Transmission Problems RAS Moscow Russia Innopolis University Russia Skolkovo Institute of Science and Technology Russia The Institute for System Programming The Russian Academy of Sciences Russia

The challenges of black box optimization arise due to imprecise responses and limited output information. This article describes new results on optimizing multivariable functions using an Order Oracle, which provides access only to the order between function values and with some small errors. We obtained convergence rate estimates for the one-dimensional search method (golden ratio method) under the condition of oracle inaccuracy, as well as convergence results for the algorithm on a "square" (also with noise), which outperforms its alternatives. The results obtained are similar to those in problems with oracles providing significantly more information about the optimized function. Additionally, the practical application of the algorithm has been demonstrated in maximizing a preference function, where the parameters are the acidity and sweetness of the drink. This function is expected to be convex or at least quasi-convex. Copyright © 2024, The Authors. All rights reserved.

关键词： Optimization algorithms

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Training Policy for Privacy-Preserving Logistic Regression in Federated Learning Environments

Training Policy for Privacy-Preserving Logistic Regression i...

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Federated Learning Technologies and Applications (FLTA), International Conference on

作者： Jorge M. Cortés-Mendoza Andrei Tchernykh Horacio González-Vélez Cloud Competency Centre National College of Ireland Dublin Ireland Computer Science Department CICESE Research Center Ensenada Mexico Institute for System Programming RAS Moscow Russia

ISBN: (数字)9798350354812

ISBN: (纸本)9798350354829

Logistic Regression (LR) is a widely used statistical model for classification problems. However, its training and evaluation in a shared environment increase the possibility of information leaking. A federated LR reduces security issues by using only locally available data for training. In a Federated Learning (FL) environment, LR receives the coefficients of local models to create the federated LR model, which is then distributed to update the local models. The exchange process does not leak confidential information when LR coefficients are encrypted. Homomorphic Encryption (HE) allows the merging of local LR models with privacy preservation (HE-LR). This work presents a novel training policy to reduce the training time with only slightly decreased quality in an FL environment with HE. We analyze the accuracy and time of FL policies with HE-LR that progressively reduce the amount of training data and exchange the LR coefficients in a privacy-preserving manner. The results show that the proposed policy can speed up the training time between 12% and 69%, compared to the traditional FL approach, with an average decrease in accuracy of 1.79% and 1.95%.

关键词： Training Measurement Logistic regression Privacy Accuracy Federated learning Merging Training data Cryptography Homomorphic encryption

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Comparative analysis of non/ductedpropeller under the influence of vertical wall

Comparative analysis of non/ductedpropeller under the influe...

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Ivannikov ISPras Open Conference (ISPras)

作者： Mengfei Wang QingXu Qin Zhang Andrey Epikhin Bingchen Liang College of Engineering Ocean University of China Qingdao China Ivannikov Institute for System Programming of the RAS Moscow Russia Shandong Provincial Key Laboratory of Ocean Engineering Qingdao China

A numerical and experimental study has been conducted to explore the influence of vertical wall on the wake of the non/ducted propeller. The numerical simulation is achieved using a structured and transient sliding mesh approach. The control equations are closed by the Delayed Detached Eddy Simulation (DDES), and the computational results are compared with the available experimental data. By dividing the ducted propeller flow wake vortex shape into different behavior regions, the temporal vortex evolution near the wake of the propellers under the influence of different vertical walls are emphatically analysed. The results show that the jet flow wake reaches the wall, forming a conical low-speed area at the centre of the wall. The fluid circulates from the outer side to the inner side of the cone, forming a vortex whose size first increases and then decreases with the distance between the propellers and the wall. In addition, the change of propellers wake velocity profile is given. The wake velocity of propeller and ducted propeller decreases exponentially and linearly along the flow direction, respectively.

关键词： Fluids Propellers Shape Computational modeling Numerical simulation Mathematical models Data models

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Docmarking: Real-Time Screen-Cam Robust Document Image Watermarking

Docmarking: Real-Time Screen-Cam Robust Document Image Water...

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Ivannikov ISPras Open Conference (ISPras)

作者： Aleksey Yakushev Yury Markin Dmitry Obydenkov Alexander Frolov Stas Fomin Manuk Akopyan Alexander Kozachok Arthur Gaynov Ivannikov Institute for System Programming of the RAS Moscow Russia Russian Federation Security Guard Service Federal Academy Oryol Russia Ministry of Defence of the Russian Federation Moscow Russia

关键词： Neural networks Watermarking Cameras Real-time systems

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