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38th Conference on Neural Information Processing Systems (NeurIPS 2024)
2024.
Under the general editorship: A. Globerson, L. Mackey, D. Belgrave, A. Fan, U. Paquet, J. Tomczak, C. Zhang
Proceedings of the international conference "Neural Information Processing Systems 2024." (NeurIPS 2024)
Chapters
Velikonivtsev F., Mironov M., Prokhorenkova L., , in: 38th Conference on Neural Information Processing Systems (NeurIPS 2024).: [б.и.], 2024. P. 57993–58022.
For many graph-related problems, it can be essential to have a set of structurally diverse graphs. For instance, such graphs can be used for testing graph algorithms or their neural approximations. However, to the best of our knowledge, the problem of generating structurally diverse graphs has not been explored in the literature. In this paper, ...
Added: October 15, 2024
Mozikov M., Severin N., Bodishtianu V. et al., , in: 38th Conference on Neural Information Processing Systems (NeurIPS 2024).: [б.и.], 2024. P. 13927–13981.
Added: November 22, 2024
Gorbunov M., Yudin N., Soboleva V. et al., , in: 38th Conference on Neural Information Processing Systems (NeurIPS 2024).: [б.и.], 2024. P. 68713–68739.
Added: November 26, 2024
Gladin E., Dvurechensky P., Mielke A. et al., , in: 38th Conference on Neural Information Processing Systems (NeurIPS 2024).: [б.и.], 2024. P. 14484–14508.
Added: November 28, 2024
Bazhenov G., Platonov O., Prokhorenkova L., , in: 38th Conference on Neural Information Processing Systems (NeurIPS 2024).: [б.и.], 2024. P. 1–26.
Tabular machine learning is an important field for industry and science. In this f ield, table rows are typically treated as independent data samples, but additional information about the relations between these samples is sometimes available and can be used to improve predictive performance. Such information can be naturally modeled with a graph, hence tabular ...
Added: December 17, 2024
Samsonov S., Moulines E., Shao Q. et al., , in: 38th Conference on Neural Information Processing Systems (NeurIPS 2024).: [б.и.], 2024. P. 12408–12460.
In this paper, we obtain the Berry–Esseen bound for multivariate normal approximation for the Polyak-Ruppert averaged iterates of the linear stochastic approximation (LSA) algorithm with decreasing step size. Our findings reveal that the fastest rate of normal approximation is achieved when setting the most aggressive step size αk ≍ k −1/2 . Moreover, we prove ...
Added: February 7, 2025
Mangold P., Samsonov S., Labbi S. et al., , in: 38th Conference on Neural Information Processing Systems (NeurIPS 2024).: [б.и.], 2024. Ch. 37 P. 13927–13981.
In this paper, we analyze the sample and communication complexity of the federated linear stochastic approximation (FedLSA) algorithm. We explicitly quantify the effects of local training with agent heterogeneity. We show that the communication complexity of FedLSA scales polynomially with the inverse of the desired accuracy ϵ. To overcome this, we propose SCAFFLSA a new ...
Added: February 11, 2025
Maxim Nikolaev, Mikhail Kuznetsov, Dmitry P. Vetrov et al., , in: 38th Conference on Neural Information Processing Systems (NeurIPS 2024).: [б.и.], 2024. P. 45600–45635.
Added: February 17, 2025
Sadrtdinov I., Kodryan M., Pokonechny E. et al., , in: 38th Conference on Neural Information Processing Systems (NeurIPS 2024).: [б.и.], 2024. P. 58445–58479.
Added: February 19, 2025
Agafonov A., Petr Ostroukhov, Mozhaev R. et al., , in: 38th Conference on Neural Information Processing Systems (NeurIPS 2024).: [б.и.], 2024. P. 115816–115860.
Variational inequalities represent a broad class of problems, including minimization and min-max problems, commonly found in machine learning. Existing second-order and high-order methods for variational inequalities require precise computation of derivatives, often resulting in prohibitively high iteration costs. In this work, we study the impact of Jacobian inaccuracy on second-order methods. For the smooth and ...
Added: July 15, 2025
Kovalev D., Ekaterina Borodich, Alexander Gasnikov et al., , in: 38th Conference on Neural Information Processing Systems (NeurIPS 2024).: [б.и.], 2024. P. 96566–96606.
We consider the task of minimizing the sum of smooth and strongly convex functions stored in a decentralized manner across the nodes of a communication network whose links are allowed to change in time. We solve two fundamental problems for this task. First, we establish {\em the first lower bounds} on the number of decentralized ...
Added: November 18, 2025
Nikita Starodubcev, Mikhail Khoroshikh, Babenko A. et al., , in: 38th Conference on Neural Information Processing Systems (NeurIPS 2024).: [б.и.], 2024. P. 12496–12527.
Diffusion distillation represents a highly promising direction for achieving faithful text-to-image generation in a few sampling steps. However, despite recent successes, existing distilled models still do not provide the full spectrum of diffusion abilities, such as real image inversion, which enables many precise image manipulation methods. This work aims to enrich distilled text-to-image diffusion models ...
Added: February 17, 2026
Keywords: machine learning
Tyukin I., Tyukina T., van Helden D. P. et al., Information Sciences 2024 Vol. 678 Article 120856
AI errors pose a significant challenge, hindering real-world applications. This work introduces a novel approach to cope with AI errors using weakly supervised error correctors that guarantee a specific level of error reduction. Our correctors have low computational cost and can be used to decide whether to abstain from making an unsafe classification. We provide ...
Added: May 23, 2026
Zaikin A., Sviridov I., Sosedka A. et al., Technologies 2026 Vol. 14 No. 2 Article 84
High-dimensional tabular data are common in biomedical and clinical research, yet conventional machine learning methods often struggle in such settings due to data scarcity, feature redundancy, and limited generalization. In this study, we systematically evaluate Synolitic Graph Neural Networks (SGNNs), a framework that transforms high-dimensional samples into sample-specific graphs by training ensembles of low-dimensional pairwise ...
Added: May 23, 2026
Kibkalo Vladislav, Chertopolokhov V., Mukhamedov A. et al., IEEE Access 2026 Vol. 14 P. 14369–14392
This study presents on-the-fly identification and multi-step prediction of nonlinear systems with delayed inputs using a dynamic neural network combined with a smooth projection onto ellipsoids. The projection enforces parameter constraints that guarantee stability, while a Lyapunov–Krasovskii analysis yields computable ultimate error bounds. Riccati-type matrix inequalities are derived, providing an efficient vectorization–projection–devectorization implementation suitable for ...
Added: May 22, 2026
Loshkareva M. E., Matveeva N., Вестник Томского государственного университета. История 2026 № 100 С. 112–118
This research is an endeavor to apply social network analysis (SNA) to the study of a medieval narrative source. The authors suppose that the use of network analysis may offer new possibilities in the study of the history of regions characterized by some political fragmentation. Authors tried to construct networks of historical interactions from 1193 ...
Added: May 22, 2026
Shipilov F., Barnyakov A., Ivanov A. et al., / Series Physics "arxiv.org". 2026.
A fast simulation of the detector response is a vital task in high-energy physics (HEP). Traditional Monte-Carlo methods form the backbone of modern particle physics simulation software but are computationally expensive. We present a machine-learning-based approach to fast simulation of the Focusing Aerogel Ring Imaging Cherenkov (FARICH) detector response. Given a particle track and momentum, ...
Added: May 19, 2026
Rabat: Association for Computational Linguistics, 2026.
Added: May 19, 2026
Bezzubov S., Malikov D., Krasnov L. et al., Scientific data 2026 Vol. 13 Article 727
Solubility is a crucial property of organic compounds, impacting their potential applications in synthetic chemistry, materials science and drug design. Moreover, in technological processes mixtures of solvents are often utilized, making the solubility assessment more complicated. Predicting solubility values in mixtures of solvents from a molecular structure can help to address this issue, although a ...
Added: May 19, 2026
Pikalov V., Meshcheryakov V., Kondratev S. et al., Technologies 2026 Vol. 14 No. 1 P. 1–27
This paper presents Aerokinesis, an IoT-based software–hardware system for intuitive gesture-driven control of quadcopter unmanned aerial vehicles (UAVs), developed within the Robot Operating System 2 (ROS2) framework. The proposed system addresses the challenge of providing an accessible human–drone interaction interface for operators in scenarios where traditional remote controllers are impractical or unavailable. The architecture comprises ...
Added: May 19, 2026
Kondratev S., Yulia Dyrchenkova, Georgiy Nikitin et al., Technologies 2026 Vol. 14 No. 1 Article 69
This paper presents Aerokinesis, an IoT-based software–hardware system for intuitive gesture-driven control of quadcopter unmanned aerial vehicles (UAVs), developed within the Robot Operating System 2 (ROS2) framework. The proposed system addresses the challenge of providing an accessible human–drone interaction interface for operators in scenarios where traditional remote controllers are impractical or unavailable. The architecture comprises ...
Added: May 19, 2026
Springer, 2025.
This book constitutes the refereed proceedings of the 19th International Conference on Parallel Computational Technologies, PCT 2025, held in Moscow, Russia, during April 8–10, 2025.
The 31 full papers included in this volume were carefully reviewed and selected from 122 submissions. These papers were organized under the following topical sections: High Performance Architectures, Tools and Technologies; ...
Added: May 18, 2026
Ronglin Z., Wei L., Jiahong C. et al., Journal of Signal Processing Systems 2026 Vol. 98 P. 1–15
To address the need for lightweight and low-latency protection in massive resource-constrained 5G Internet of Things (IoT) systems, this paper proposes Key-Controlled Modulation Hopping and Constellation Rotation (KMHCR). KMHCR is designed as a physical-layer confidentiality-enhancement mechanism that avoids bit-wise full-payload encryption in the protection pipeline. It uses a shared key derived from channel-reciprocity secret key ...
Added: May 16, 2026
Suvorov N. M., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 3(2) P. 49–66
Data Petri Nets (DPNs) extend classical Petri nets to model processes where data directly influences control-flow, enabling a comprehensive view of system behavior and possibility to detect failure points that could otherwise be hidden. Soundness is a correctness criterion that captures such failure points as deadlocks and livelocks as well as model boundedness and absence ...
Added: May 16, 2026
Xiong N., Long W., He D. et al., Algorithms 2026 Vol. 19 No. 5 Article 386
In the era of data-driven education, educational social networks generate large volumes of high-dimensional and complex-structured data through learner interactions, collaborative activities, and resource-sharing behaviors, posing significant challenges to traditional unsupervised learning methods. Such data often exhibit non-convex distributions, heterogeneity, and noise sensitivity, making conventional clustering approaches insufficient for capturing their intrinsic structural relationships. To ...
Added: May 13, 2026
Velichkov B., Nikolova-Koleva I., Slavcheva M., Shumen: INCOMA Ltd, 2025.
The RANLP 2025 Student Research Workshop (RANLPStud’2025) is a special track of the established international conference Recent Advances in Natural Language Processing (RANLP’2025).
The RANLPStud is being organised for the 9th time and this year is running in parallel with the other tracks of the main RANLP 2025 conference. The target of RANLPStud’25 is to be a ...
Added: May 12, 2026
Stepanyants V., Долгов И. М., Хорошилов Г. С. et al., Труды Института системного программирования РАН 2026 Т. 38 № 3 С. 95–110
Highly automated and connected vehicles are gradually entering the market. Currently, solutions are being proposed that allow these technologies to be used for cooperative driving automation, which can significantly improve traffic safety. Such technologies and their software should be tested to ensure safety before being implemented in real systems. Verification and validation of vehicular control ...
Added: May 12, 2026
Tikhonov R., Efendiev M. T., Fedotenkov A. A., 2026 International Russian Smart Industry Conference (SmartIndustryCon) 2026 P. 542–547
High-fidelity simulation environments like CARLA and ROS are essential for connected and automated vehicle research. They allow researchers to verify and validate new software and technology without the time, financial, and safety overheads of real-world testing. However, their operation requires considerable expertise for creating platform-specific scenario configuration files, which complicates the research workflow. This paper ...
Added: May 11, 2026
Los Alamitos: IEEE Computer Society, 2026.
It is a great pleasure for us to welcome you on behalf of the conference committees, to the 11th IEEE International Conference on Smart Cloud (IEEE SmartCloud 2026), we are glad that we can have this international conference in New York city, USA. Now, please allow us to introduce the IEEE SmartCloud 2026 conference. The ...
Added: May 10, 2026
Avdoshin S. M., Pesotskaya E. Y., Информационные технологии 2026 Т. 32 № 4 С. 185–194
With the rapid advancement of artificial intelligence, and deep learning in particular, models have emerged that are capable of delivering highly accurate predictions. However, the internal logic of such models remains difficult to interpret—an issue of critical importance, especially in domains where the correctness of an algorithm directly affects high-stakes decision-making. One promising avenue for ...
Added: May 8, 2026
Avdoshin S. M., Pesotskaya E. Y., Business Informatics 2026 Vol. 20 No. 1 P. 7–28
The rapid development of artificial intelligence (AI) is accompanied by increasing computational
complexity and decreasing model transparency, which significantly limits its adoption in critical
domains that require a high level of trust, interpretability, and justification of decisions. Under these
conditions, the field of Explainable Artificial Intelligence (XAI) has gained particular importance as it
focuses on approaches and technologies that ...
Added: May 8, 2026
Varnavsky A., IEEE Access 2026 Vol. 14 P. 37487–37508
Puzzles are an excellent tool for learning computer science and programming, fostering increased interest, engagement, and motivation among students, as well as developing logical, critical, and computational thinking. Among beginner programmers, Parson's Programming Puzzles are quite popular, aimed at mastering the basic syntactic and logical constructs of programming languages. However, as students' skills grow, their ...
Added: May 7, 2026
Krasnov L., Malikov D., Kiseleva M. et al., Journal of Medicinal Chemistry 2026 Vol. 69 No. 8 P. 8838–8851
In this work, we developed a straightforward data-driven approach to predict the cytotoxicity of metal complexes based entirely on their (metal + ligands) composition. To this end, we have manually curated MetalCytoToxDB─a comprehensive experimental database comprising 26,500 IC50 values for 7050 metal complexes against 754 cell lines from 1921 articles. Based on these, machine learning ...
Added: April 23, 2026
Plesovskikh A., Journal of Applied Economic Research 2023 Т. 22 № 2 С. 323–354
Modern studies widely discuss the role of special economic zones in stimulating the economic growth and development of Russia, generating the necessary investment flows and increasing the country's innovative potential by expanding production in high-tech sectors of the economy with high added value. The purpose of the study is to model the process of generating ...
Added: April 13, 2026
Pakshin P., Legal Issues in the Digital Age 2026 Vol. 7 No. 1 P. 32–48
Artificial intelligence plays a significant role in automation, minimizing human intervention in fields such as medicine, art, and law. Despite the historically close relationship between art and technology, generative AI has expanded the potential for creative activity. A significant catalyst for this process has been the proliferation of pre-trained AI systems, which have accelerated the ...
Added: March 31, 2026