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Annual Conference on Information sciences and Systems (CISS)

作者： Sam Leone Xingzhi Sun Michael Perlmutter Smita Krishnaswamy Program for Applied Mathematics Yale University Department of Computer Science Yale University Department of Mathematics Boise State University Department of Genetics Yale School of Medicine Wu Tsai Institute Yale University FAIR Meta AI Computational Biology and Bioinformatics Program Yale University

Here we consider the problem of denoising features associated to complex data, modeled as signals on a graph, via a smoothness prior. This is motivated in part by settings such as single-cell RNA where the data is very high-dimensional, but its structure can be captured via an affinity graph. This allows us to utilize ideas from graph signal processing. In particular, we present algorithms for the cases where the signal is perturbed by Gaussian noise, dropout, and uniformly distributed noise. The signals are assumed to follow a prior distribution defined in the frequency domain which favors signals which are smooth across the edges of the graph. By pairing this prior distribution with our three models of noise generation, we propose Maximum A Posteriori (M.A.P.) estimates of the true signal in the presence of noisy data and provide algorithms for computing the M.A.P. Finally, we demonstrate the algorithms’ ability to effectively restore signals from white noise on image data and from severe dropout in single-cell RNA sequence data.

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Matrix Structure of Classical Z2×Z2 Graded Lie Algebras

Matrix Structure of Classical Z2×Z2 Graded Lie Algebras

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International Workshop on Lie Theory and Its Applications in Physics, LT 2023

作者： Stoilova, N.I. Van der Jeugt, J. Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Boul. Tsarigradsko Chaussee 72 Sofia1784 Bulgaria Department of Applied Mathematics Computer Science and Statistics Ghent University Krijgslaan 281-S9 Gent9000 Belgium

ISBN: (纸本)9789819764525

A Z2×Z2-graded Lie algebra g is a Z2×Z2-graded algebra g with a bracket [[·,·]] that satisfies certain graded versions of the symmetry and Jacobi identity. In particular, despite the common terminology, g is not a Lie algebra. We construct classes of Z2×Z2-graded Lie algebras corresponding to the classical Lie algebras, in terms of their defining matrices. For the Z2×Z2-graded Lie algebra of type A, the construction coincides with the previously known class. For the Z2×Z2-graded Lie algebra of type B, C and D our construction is new and gives rise to interesting defining matrices closely related to the classical ones but undoubtedly different. We also give some examples and possible applications to parastatistics. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Matrix algebra

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Comparative analysis of distance metrics for intuitionistic fuzzy sets in multi-criteria decision analysis 28th

Comparative analysis of distance metrics for intuitionistic ...

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28th International Conference on Knowledge Based and Intelligent information and Engineering Systems, KES 2024

作者： Wieckowski, Jakub Niewiadomski, Daniel Kulis, Dominik Salabun, Wojciech National Institute of Telecommunications ul. Szachowa 1 Warsaw04-894 Poland Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology Szczecin ul. Zolnierska 49 Szczecin71-210 Poland Department of Computer Science Faculty of Computer Science and Telecommunications Cracow University of Technology Warszawska 24 Krakow31-155 Poland

This paper presents a comparative analysis of selected distance metrics within the intuitionistic fuzzy environment in Multi-Criteria Decision Analysis (MCDA). The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, combined with intuitionistic fuzzy sets (IFS), was employed to investigate how different distance metrics influence decision-making outcomes. The study examines the sensitivity of the obtained recommendations to the variation in the calculation formula used to determine the distance between two IFS. The practical problem of selecting a site for a large-scale rooftop photovoltaic project served as the case study for this comparison. The results indicated that using different distance metrics within the IF-TOPSIS method led to varying preference score ranges and differing rankings, particularly in the middle portions of the rankings. The findings underscore the sensitivity of MCDA methods to the choice of distance metrics used in the calculation process. © 2024 The Authors.

关键词： Fuzzy models

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Building Footprint Extraction in Dense Areas using Super Resolution and Frame Field Learning 12

Building Footprint Extraction in Dense Areas using Super Res...

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12th International Conference on Awareness science and Technology, iCAST 2023

作者： Nguyen, Vuong Ho, Trong-Anh Vu, Duc-Anh Ngoc Anh, Nguyen Thi Thang, Tran Ngoc Department of Computer Science University of Houston HoustonTX United States Skymap Global Hanoi Viet Nam Nanyang Technological University Singapore School of Applied Mathematics and Informatics Hanoi University of Science and Technology Hanoi Viet Nam

ISBN: (纸本)9798350324693

Despite notable results on standard aerial datasets, current state-of-the-arts fail to produce accurate building footprints in dense areas due to challenging properties posed by these areas and limited data availability. In this paper, we propose a framework to address such issues in polygonal building extraction. First, super resolution is employed to enhance the spatial resolution of aerial image, allowing for finer details to be captured. This enhanced imagery serves as input to a multitask learning module, which consists of a segmentation head and a frame field l earning h ead t o e ffectively h andle t he irregular building structures. Our model is supervised by adaptive loss weighting, enabling extraction of sharp edges and fine-grained polygons which is difficult due to overlapping buildings and low data quality. Extensive experiments on a slum area in India that mimics a dense area demonstrate that our proposed approach significantly outperforms the current state-of-the-art methods by a large margin. © 2023 IEEE.

关键词： Extraction

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Application of COPRAS, PROMETHEE, and EDAS methods in sustainable energy development: A comparative study case 28th

Application of COPRAS, PROMETHEE, and EDAS methods in sustai...

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28th International Conference on Knowledge Based and Intelligent information and Engineering Systems, KES 2024

作者： Wieckowski, Jakub Gajewski, Pawel Swaldek, Krzysztof Salabun, Wojciech National Institute of Telecommunications ul. Szachowa 1 Warsaw04-894 Poland Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology Szczecin ul. Zolnierska 49 Szczecin71-210 Poland Department of Computer Science Faculty of Computer Science and Telecommunications Cracow University of Technology Warszawska 24 Krakow31-155 Poland

This paper provides a comparative analysis of three selected Multi-Criteria Decision Analysis (MCDA) methods in a practical decision problem to examine the robustness of the obtained results. The Complex Proportional Assessment (COPRAS), Preference Ranking Organization METHod for Enrichment of Evaluations (PROMEHTEE) II, and Evaluation based on Distance from Average Solution (EDAS) methods were utilized for the evaluation purposes, while the Ranking Comparison (RANCOM) method was applied to determine criteria weights. The application was directed toward sustainable development management in selected European countries considering different energy sources in the consumption share per capita. The obtained results showed, that depending on the used MCDA method, the ranking of countries differed, thus showing that the evaluation process is sensitive to changing assessment methods. © 2024 The Authors.

关键词： Sustainable development goals

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Efficient Approximation of Asymmetric Shapley Values Using Functional Decomposition 1

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Machine Learning and Knowledge Extraction 7th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2023

作者： Gevaert, Arne Saranti, Anna Holzinger, Andreas Saeys, Yvan Department of Applied Mathematics Computer Science and Statistics Ghent University Ghent9000 Belgium VIB Center for Inflammation Research Ghent9000 Belgium University of Natural Resources and Life Sciences Vienna Austria

ISBN: (数字)9783031408373

ISBN: (纸本)9783031408366

Asymmetric Shapley values (ASVs) are an extension of Shapley values that allow a user to incorporate partial causal knowledge into the explanation process. Unfortunately, computing ASVs requires sampling permutations, which quickly becomes computationally expensive. We propose A-PDD-SHAP, an algorithm that employs a functional decomposition approach to approximate ASVs at a speed orders of magnitude faster compared to permutation sampling, which significantly reduces the amortized complexity of computing ASVs when many explanations are needed. Apart from this, once the A-PDD-SHAP model is trained, it can be used to compute both symmetric and asymmetric Shapley values without having to re-train or re-sample, allowing for very efficient comparisons between different types of explanations. © 2023, The Author(s).

关键词： Asymmetric Shapley values Functional Decomposition Shapley values

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On the Existence of Highly Organized Communities in Networks of Locally Interacting Agents 7th

On the Existence of Highly Organized Communities in Netwo...

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7th International Symposium on Cyber Security, Cryptology, and Machine Learning, CSCML 2023

作者： Liagkou, Vasiliki Nastou, Panagiotis E. Spirakis, Paul Stamatiou, Yannis C. Computer Technology Institute and Press - "Diophantus" University of Patras Campus Patras26504 Greece Department of Computer Science University of Liverpool Liverpool United Kingdom Department of Business Administration University of Patras Patras26504 Greece Department of Informatics and Telecommunications University of Ioannina Kostakioi Arta47100 Greece Department of Mathematics Applied Mathematics and Mathematical Modeling Laboratory University of the Aegean Samos Greece Center for Applied Optimization University of Florida Gainesville United States

ISBN: (纸本)9783031346705

In this paper we investigate phenomena of emergence of highly organized structures in networks. Our approach is based on Kolmogorov complexity of networks viewed as finite size strings. We apply this approach to study the emergence of simple organized, hierarchical, structures based on Sierpinski Graphs and we prove a Ramsey type theorem that bounds the number of vertices in Kolmogorov random graphs that contain Sierpinski Graphs as subgraphs. Moreover, we show that Sierpinski Graphs encompass close-knit relationships among their vertices that facilitate fast spread and learning of information. In the context of our work we can investigate questions related to the emergence or formation of suitably large groups of malicious individuals in a networks of interacting agents, which are able to take control of the networks. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Graphic methods

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Stability analysis of nonlinear stochastic flexibility function in smart energy systems

arXiv

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arXiv 2024年

作者： Tohidi, Seyed Shahabaldin Ritschel, Tobias K.S. Tsaousoglou, Georgios Thygesen, Uffe Høgsbro Madsen, Henrik Department of Applied Mathematics and Computer Science Technical University of Denmark Kgs. LyngbyDK-2800 Denmark

Demand-side management provides a great potential for improving the efficiency and reliability of energy systems. This requires a mechanism to connect the market level and the demand side. The flexibility function is a novel approach that bridges the gap between the markets and the dynamics of physical assets at the lower levels of the energy systems and activates demand-side flexibility with the purpose of decision-making as well as for offering a new framework for balancing and grid services. Employing this function as a key for many decision-making and control algorithms reveals that a mathematically rigorous stability analysis is required for it. In this paper, we investigate the stability properties of two nonlinear flexibility functions, as a dynamic mapping between electricity price and power consumption. Specifically, we analyze the stability of a deterministic flexibility function and an Itô stochastic flexibility function. Simulation results are also provided to demonstrate the dynamics of the flexibility functions and to show that the analytical results hold. Copyright © 2024, The Authors. All rights reserved.

关键词： Stochastic systems

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A Fused Machine Learning Approach for Intrusion Detection System

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computers, Materials & Continua 2023年第2期74卷 2607-2623页

作者： Muhammad Sajid Farooq Sagheer Abbas Atta-ur-Rahman Kiran Sultan Muhammad Adnan Khan Amir Mosavi School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam 31441Saudi Arabia Department of CIT The Applied CollegeKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Software Gachon UniversitySeongnam13120Korea John von Neumann Faculty of Informatics Obuda UniversityBudapest1034Hungary Institute of Information Engineering Automation and MathematicsSlovak University of Technology in BratislavaBratislava81107Slovakia Faculty of Civil Engineering TU-DresdenDresden01062Germany

The rapid growth in data generation and increased use of computer network devices has amplified the infrastructures of *** interconnectivity of networks has brought various complexities in maintaining network availability,consistency,and *** learning based intrusion detection systems have become essential to monitor network traffic for malicious and illicit *** intrusion detection system controls the flow of network traffic with the help of computer *** deep learning algorithms in intrusion detection systems have played a prominent role in identifying and analyzing intrusions in network *** this purpose,when the network traffic encounters known or unknown intrusions in the network,a machine-learning framework is needed to identify and/or verify network *** Intrusion detection scheme empowered with a fused machine learning technique(IDS-FMLT)is proposed to detect intrusion in a heterogeneous network that consists of different source networks and to protect the network from malicious *** proposed IDS-FMLT system model obtained 95.18%validation accuracy and a 4.82%miss rate in intrusion detection.

关键词： Fused machine learning heterogeneous network intrusion detection

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Numerical optimal control for delay differential equations: A simultaneous approach based on linearization of the delayed state

arXiv

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arXiv 2024年

作者： Ritschel, Tobias K.S. Stange, Søren Department of Applied Mathematics and Computer Science Technical University of Denmark Kgs. LyngbyDK-2800 Denmark

Time delays are ubiquitous in industry, and they must be accounted for when designing control strategies. However, numerical optimal control (NOC) of delay differential equations (DDEs) is challenging because it requires specialized discretization methods and the time delays may depend on the manipulated inputs or state variables. Therefore, in this work, we propose to linearize the delayed states around the current time. This results in a set of implicit differential equations, and we compare the steady states and the corresponding stability criteria of the DDEs and the approximate system. Furthermore, we propose a simultaneous approach for NOC of DDEs based on the linearization, and we discretize the approximate system using Euler's implicit method. Finally, we present a numerical example involving a molten salt nuclear fission reactor. Copyright © 2024, The Authors. All rights reserved.

关键词： Stability criteria

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