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Cubic Spline Interpolation Approach to Solve Multi-Choice Programming Problem
International Journal of Applied and Computational Mathematics. 2022. Vol. 9. No. 1. Article 6.
Dutta S., Kaur A.
Multi-choice has become a significant part of the real-life decision-making process. Most
of the problems involve more than one parameter as a choice, and among those different
choices only one choice is to be made, which will optimize the objective function. The
difficulty in making such a choice can be at ease with the help of mathematical techniques.
In this paper, we propose a novel solution procedure to handle the multi-choice parameters
in the constraint using cubic spline interpolation method. After analyzing the results, we
observed that the proposed method yields better results as compared to existing methods.
Two numerical examples are presented to explain the method and validate the fact of complete
utilization of the resources
Buryak A., Tessler R., Troshkin M., Journal of Geometry and Physics 2026 Vol. 223 Article 105783
We give a natural definition of open Hurwitz numbers, where the weight of each ramified covering includes an integer parameter N taken to the power that is equal to the number of boundary components of a Riemann surface with boundary mapping to . We prove that the resulting sequence of partition functions, depending on , is a tau-sequence of ...
Added: June 19, 2026
Buryak A., Rossi P., Communications in Mathematical Physics 2025 Vol. 406 Article 205
Of the two approaches to integrable systems associated to semisimple cohomological field theories (CohFTs), the one suggested by Dubrovin and Zhang and the more recent one using the geometry of the double ramification (DR) cycle, the second has the advantage of being very explicit. The Poisson operator of the DR hierarchy is , where is the metric ...
Added: June 19, 2026
Cherednichenko O., Herbert A., Poptsova M., Computational and Structural Biotechnology Journal 2025 Vol. 27 P. 992–1000
Large language models (LLMs) in genomics have successfully predicted various functional genomic elements. While their performance is typically evaluated using genomic benchmark datasets, it remains unclear which LLM is best suited for specific downstream tasks, particularly for generating whole-genome annotations. Current LLMs in genomics fall into three main categories: transformer-based models, long convolution-based models, and state-space models ...
Added: June 19, 2026
Poptsova M., Briefings in Bioinformatics 2025 Vol. 26 No. 2 P. 1–11
Kolmogorov–Arnold networks (KANs) emerged as a promising alternative for multilayer perceptrons (MLPs) in dense fully connected networks. Multiple attempts have been made to integrate KANs into various deep learning architectures in the domains of computer vision and natural language processing. Integrating KANs into deep learning models for genomic tasks has not been explored. Here, we ...
Added: June 19, 2026
Vukovic N., Аверина А. О., Стефанова К. А., Анализ и прогноз. Журнал ИМЭМО РАН 2026 № 1 С. 26–39
Responsible business conduct and environmental, social, and governance (ESG) policies play a crucial role in advancing the global sustainable development agenda. As businesses worldwide integrate sustainability into their strategic frameworks, ESG ratings serve as key instruments for assessing corporate responsibility and guiding investment decisions. This paper conducts a comparative analysis of major international ESG ratings ...
Added: June 19, 2026
Анненков А. Н., Nesterov R., Моделирование и анализ информационных систем 2026 Т. 33 № 2 С. 176–205
Declarative process models are widely used in process mining to describe flexible process behavior through sets of constraints. However, models discovered automatically from event logs may contain inconsistent constraints, which can make them difficult to interpret and unusable for execution, conformance checking, or further analysis. Existing methods for consistency analysis either rely on automata-based constructions ...
Added: June 18, 2026
Cham: Springer Publishing Company, 2026.
The four-volume set LNCS 16483-16486 constitutes the refereed conference proceedings of the 48th European Conference on Information Retrieval, ECIR 2026, held in Delft, The Netherlands, during March 29–April 2, 2026.
The 46 full papers and 37 short papers presented together with 10 findings papers, 9 reproducibility papers, 17 resource papers, 11 workshop papers, 7 tutorial papers, ...
Added: June 18, 2026
Poddiakov A., Троицкий вариант. Наука 2026 № 12 С. 24–25
В научно-популярной заметке представлен обзор содержания поста филдсовского медалиста Тимоти Гауэрса о возможностях ИИ в математике и содержания комментариев под постом. Обзор сделан в основном чат-ботом DeepSeek. В заключение обсуждается возможность не только решения задач искусственным интеллектом, но и их постановки. ...
Added: June 18, 2026
Beznosikov A., Kormakov G., Grigorievskiy A. et al., Journal of Optimization Theory and Applications 2026 Vol. 209 Article 18
The objective of Vertical Federated Learning (VFL) is to collectively train a model using features available on different devices while sharing the same users. This paper focuses on the saddle point reformulation of the VFL problem via the classical Lagrangian function. We first demonstrate how this formulation can be solved using deterministic methods.More importantly, we explore various stochastic modifications to ...
Added: June 17, 2026
Воронина В., Tkachuk A., Финансовый менеджмент 2026 № 5 С. 128–134
The article examines the impact of sanctions and trade-related economic restrictions imposed by the United States during the Trump administration on China’s macroeconomic dynamics and its position in the global economy. The purpose of the study is to assess how external pressure affected GDP growth, foreign trade, and investment activity, as well as to identify ...
Added: June 17, 2026
Garzón J., Mora Rodríguez J., Moreno-Franco H. A., Applied Mathematics and Optimization 2026 Vol. 94 No. 10 P. 1–43
We study an optimal extraction problem where the agent’s actions in the spot market exert an additive proportional negative impact on the commodity price. The commodity price dynamics, prior to any activity by the agent, evolve according to a drifted Brownian motion with jumps. The agent’s primary aim is to identify an optimal extraction strategy ...
Added: June 17, 2026
Shirokova Galina, Veksler Kseniia, Dvorkina Daria et al., International Entrepreneurship and Management Journal 2026 Vol. 22 No. 3 Article 106
This article investigates how a scientific approach to entrepreneurial decisionmaking shapes the performance of student-founded new ventures across countries through the psychological resource of founder resilience and varying institutional conditions. Building on the theory-based view, psychological capital theory, and an institutional perspective, the study conceptualizes scientific decision-making as a deliberate, evidence-oriented logic that entrepreneurs employ ...
Added: June 17, 2026
Chertenkov V. I., Shchur L., Lobachevskii Journal of Mathematics 2026 Vol. 47 No. 2 P. 720–727
Supervised machine learning is successfully applied to the study of critical phenomena and allows us to obtain a numerical estimate of the phase transition temperature and the correlation length exponent. We discuss the influence of possible systematic errors, as well as statistical errors, on the accuracy of such numerical estimates. Errors in the training and ...
Added: June 16, 2026
Deeb B., Andrey V. Savchenko, Makarov I., IEEE Access 2026 Vol. 13 P. 56283–56295
Speech Emotion Recognition has gained considerable attention in speech processing and machine learning due to its potential applications in human-computer interaction, mental health monitoring, and customer service. However, state-of-the-art models for speech emotion recognition use many parameters, which leads to computational complexity. In this paper, we introduce a novel deep-learning model to enhance the accuracy ...
Added: June 16, 2026
Makarov N., Savchenko A., Zemtsova I. et al., Scientific Reports 2025 Vol. 15 Article 26641
The grey wolf (Canis lupus) is a pivotal species for ecological studies. As a key participant in ecosystem
processes, it also serves as a model for investigating social structure formation and ecological
adaptation. However, the species’ complex social behavior, spatial dynamics, and expansive habitats
make monitoring and population assessments across large areas particularly challenging. In recent
years, audio traps ...
Added: June 16, 2026
Vasilev R., Savchenko A., Blinov P. et al., Frontiers in Medicine 2026 Vol. 13
Automated disease screening systems face challenges when applied to multi-class medical image analysis, particularly under severe class imbalance inherent in clinical datasets. Retinal fundus imaging enables non-invasive screening for multiple ocular and systemic diseases simultaneously, yet current automated systems typically assess risk for only a single pathology or a limited disease range. We developed a ...
Added: June 16, 2026
Novopoltsev M., Tulenkov A., Murtazin R. et al., IEEE Access 2025 Vol. 13 P. 188170–188181
Video-based Isolated Sign Language Recognition (ISLR) problem presents significant challenges in scaling across diverse languages due to data scarcity and the computational costs associated with training of language-specific models. In this paper, we introduce a novel training pipeline that leverages self-supervised learning on a large-scale sign language dataset. To obtain the foundation model, we utilize ...
Added: June 16, 2026
Popov K., Писчикова Е. А., Российский журнал менеджмента 2026 Т. 24 № 1 С. 45–70
Purpose: this study aims to assess the impact of independent directors’ characteristics on voluntary ESG disclosure by Russian public non-financial companies. Methodology: this study conducts an econometric analysis of panel data on 56 large Russian public non-financial companies listed on the Moscow Stock Exchange, which published standalone ESG and sustainability reports from 2017 to 2023. Findings: the significant positive impact ...
Added: June 16, 2026
Shishkina E., Revista Internacional de Metodos Numericos para Calculo y Diseno en Ingenieria 2025
This article investigates the problem of approximating the generalized
Erdélyi-Kober fractional operator (often referred to as the Lowndes operator)
using cubic splines. A method based on cubic spline interpolation
is proposed for approximating the operator on a non-uniform grid. The
convergence rate of the proposed method is proven, and its stability is
analyzed. Error bounds are established for functions in ...
Added: March 2, 2026
Enatskaya N., Вестник Южно-Уральского государственного университета, серия «Математическое моделирование и программирование» 2020 Т. 13 № 3 С. 103–111
An enumerative method is proposed for the analysis of combinatorial schemes in the
pre-asymptotic region of variation of their parameters based on the construction of their
probabilistic mathematical model, which represents for each scheme an iterative
random process of sequential non-repeated formation of all its outcomes with a certain
discipline of their numbering by unitary addition of certain elements ...
Added: October 17, 2020
Vorontsov K. V., Kochedykov D., Apishev M. et al., IEEE Computer Society, 2017.
Topic modelling is an area of text mining that has been actively developed in the last 15 years. A probabilistic topic model extracts a set of hidden topics from a collection of text documents. It defines each topic by a probability distribution over words and describes each document with a probability distribution over topics. In ...
Added: December 6, 2019
Figurnov M., Sobolev A., Vetrov D., Bulletin of the Polish Academy of Sciences: Technical Sciences 2018 Vol. 66 No. 6 P. 811–820
We present a probabilistic model with discrete latent variables that control the computation time in deep learning models such as ResNets and LSTMs. A prior on the latent variables expresses the preference for faster computation. The amount of computation for an input is determined via amortized maximum a posteriori (MAP) inference. MAP inference is performed ...
Added: February 27, 2019
Мальтина Л. П., Malafeev A., , in: Supplementary Proceedings of the 7th International Conference on Analysis of Images, Social Networks and Texts (AIST-SUP 2018), Moscow, Russia, July 5-7, 2018.: Aachen: CEUR Workshop Proceedings, 2018. Ch. 9 P. 85–94.
The paper considers the task of the morphemic analysis of Russian words and compares the efficiency of several proposed models. These models can be divided into three groups: derivational and inflectional rule-based, proba- bilistic, and hybrid models. The latter achieved state-of-the-art results of 0.848 F-score on a test set of 500 Russian words. The models ...
Added: February 15, 2019
Ni X., Quadrianto N., Wang Y. et al., , in: Proceedings of Machine Learning Research. Proceedings of the International Conference on Machine Learning (ICML 2017)Vol. 70.: Sydney: [б.и.], 2017. P. 2622–2631.
Конференция Computer Science уровня A* по рейтингу CORE
Clustering data with both continuous and discrete attributes is a challenging task. Existing methods lack a principled probabilistic formulation. In this paper, we propose a clustering method based on a tree-structured graphical model to describe the generation process of mixed-type data. Our tree-structured model factorized into a product ...
Added: December 10, 2018