Suchergebnisse - "message-passing algorithms"

Adaptive Policy-Oriented Cybersecurity: A Decentralized Framework Using Message Passing Algorithms for Dynamic Threat Mitigation

Autoren: Spyridon Evangelatos Eleni Veroni Mariza Konidi et al.

Quelle: IEEE Access, Vol 13, Pp 65216-65231 (2025)

Schlagwörter: Adaptive cybersecurity, policy-based security, threat detection, message passing algorithms, Electrical engineering. Electronics. Nuclear engineering, decentralized decision-making, TK1-9971

Zugangs-URL: https://doaj.org/article/83e9e0fa89e14395bd9dd4cc13005e88

Fourier Analysis of Iterative Algorithms

Autoren: Jones, Chris Pesenti, Lucas Chris Jones and Lucas Pesenti

Weitere Verfasser: Jones, Chris Pesenti, Lucas Chris Jones and Lucas Pesenti

Schlagwörter: Iterative Algorithms, Message-passing Algorithms, Random Matrix Theory

Dateibeschreibung: application/pdf

Relation: Is Part Of LIPIcs, Volume 334, 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025); https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2025.102

Verfügbarkeit: https://doi.org/10.4230/LIPIcs.ICALP.2025.102
https://nbn-resolving.org/urn:nbn:de:0030-drops-234791
https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2025.102

Scaling Probabilistic Inference Through Message Contraction Optimization

Autoren: Roa-Villescas, Martin Liu, Jin-Guo Wijnings, Patrick W.A. et al.

Quelle: 2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE). :123-130

Schlagwörter: Bayesian networks, probabilistic graphical models, 0202 electrical engineering, electronic engineering, information engineering, probabilistic inference, 02 engineering and technology, message-passing algorithms, 0101 mathematics, 01 natural sciences

Advancing Graph Neural Networks for Complex Relational Learning: A Multi-Scale Heterogeneity-Aware Framework with Adversarial Robustness and Interpretable Analysis

Autoren: Hao Yang Yunhong Zhou Xianzhe Ji et al.

Quelle: Mathematics, Vol 13, Iss 18, p 2956 (2025)

Schlagwörter: graph neural networks, heterogeneous graph learning, message-passing algorithms, adversarial robustness, heterophily detection, interpretable machine learning, Mathematics, QA1-939

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/2227-7390/13/18/2956; https://doaj.org/toc/2227-7390

Zugangs-URL: https://doaj.org/article/1ca799e116a8409c9b84e64d2886ef9b

Sketching Sparse Low-Rank Matrices With Near-Optimal Sample- and Time-Complexity Using Message Passing

Autoren: Xiaoqi Liu Ramji Venkataramanan Apollo - University of Cambridge Repository

Weitere Verfasser: Xiaoqi Liu Ramji Venkataramanan Apollo - University of Cambridge Repository

Quelle: IEEE Transactions on Information Theory. 69:6071-6097

Schlagwörter: Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Science - Information Theory, Information Theory (cs.IT), E.4, low-rank matrix estimation, 02 engineering and technology, peeling decoder, 01 natural sciences, sparse graph codes, 0202 electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing, 0101 mathematics, Message passing algorithms, compressed sensing

Dateibeschreibung: application/pdf

Zugangs-URL: http://arxiv.org/abs/2205.06228
https://www.repository.cam.ac.uk/handle/1810/349685
https://doi.org/10.1109/tit.2023.3273181

Fourier Analysis of Iterative Algorithms

Autoren: Jones, Chris Pesenti, Lucas Chris Jones and Lucas Pesenti

Weitere Verfasser: Jones, Chris Pesenti, Lucas Chris Jones and Lucas Pesenti

Schlagwörter: FOS: Computer and information sciences, Computer Science - Computational Complexity, Message-passing Algorithms, Random Matrix Theory, Computer Science - Data Structures and Algorithms, FOS: Mathematics, Mathematics - Combinatorics, Data Structures and Algorithms (cs.DS), Combinatorics (math.CO), ddc:004, Iterative Algorithms, Computational Complexity (cs.CC)

Dateibeschreibung: application/pdf

Zugangs-URL: http://arxiv.org/abs/2404.07881
https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2025.102

Information Bottleneck Message Passing for Military Applications

Autoren: Jan Lewandowsky Marc Adrat Gerhard Bauch

Quelle: 2021 International Conference on Military Communication and Information Systems (ICMCIS). :1-8

Schlagwörter: information bottleneck method, MLE@TUHH, channel decoding, message passing algorithms, quantization

Zugangs-URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=9486405
http://xplorestaging.ieee.org/ielx7/9486286/9486305/09486405.pdf?arnumber=9486405

Sparse representations, inference and learning

Autoren: Lauditi, Clarissa Troiani, Emanuele Mezard, Marc

Weitere Verfasser: Lauditi, Clarissa Troiani, Emanuele Mezard, Marc

Schlagwörter: CAVITY AND REPLICA METHOD, MACHINE LEARNING, MESSAGE-PASSING ALGORITHMS, PHASE DIAGRAMS

Dateibeschreibung: ELETTRONICO

Relation: info:eu-repo/semantics/altIdentifier/wos/WOS:001345860600001; firstpage:104001; lastpage:-; journal:JOURNAL OF STATISTICAL MECHANICS: THEORY AND EXPERIMENT; https://hdl.handle.net/11565/4069847

Verfügbarkeit: https://hdl.handle.net/11565/4069847
https://doi.org/10.1088/1742-5468/ad292e
https://iopscience.iop.org/article/10.1088/1742-5468/ad292e

Message-passing on hypergraphs: detectability, phase transitions and higher-order information

Autoren: Ruggeri, Nicolò Lonardi, Alessandro De Bacco, Caterina

Quelle: Journal of Statistical Mechanics: Theory and Experiment, 2024 (4)

Schlagwörter: inference of graphical models, message-passing algorithms, statistical inference

Dateibeschreibung: application/application/pdf

Relation: info:eu-repo/semantics/altIdentifier/wos/001206605800001; http://hdl.handle.net/20.500.11850/670511

Verfügbarkeit: https://hdl.handle.net/20.500.11850/670511
https://doi.org/10.3929/ethz-b-000670511

Geometric Deep Learning for Computer Vision and Image Analysis: A Survey of Recent Advances and Future Directions

Autoren: Suresh A. J.

Quelle: International Journal of Intelligent Systems and Applications in Engineering; Vol. 12 No. 1 (2024); 847 – 853

Schlagwörter: Geometric Deep Learning, Computer Vision, Image Analysis, Graph Neural Networks, 3D Shape Analysis, Spectral Methods, Message-Passing Algorithms

Dateibeschreibung: application/pdf

Zugangs-URL: https://www.ijisae.org/index.php/IJISAE/article/view/7035

Modeling and Mitigating Errors in Belief Propagation for Distributed Detection

Autoren: Abdi, Younes Ristaniemi Tapani

Quelle: IEEE Transactions on Communications. 69:3286-3297

Schlagwörter: distributed systems, ta113, hajautetut järjestelmät, FOS: Computer and information sciences, factor graphs, ta213, signaalinkäsittely, Computer Science - Information Theory, Information Theory (cs.IT), linear data-fusion, sensoriverkot, cooperative communications, 02 engineering and technology, communication errors, Tietotekniikka, computation errors, langaton tiedonsiirto, optimointi, Mathematical Information Technology, algoritmit, 0202 electrical engineering, electronic engineering, information engineering, likelihood-ratio test, blind signal processing, message-passing algorithms

Dateibeschreibung: application/pdf; fulltext

Zugangs-URL: https://ieeexplore.ieee.org/ielx7/26/9433469/09345722.pdf
http://arxiv.org/abs/2004.05220
http://juuli.fi/Record/0378690021
https://doi.org/10.1109/TCOMM.2021.3056679
http://ieeexplore.ieee.org/document/9345722
https://jyx.jyu.fi/handle/123456789/75927
https://dblp.uni-trier.de/db/journals/tcom/tcom69.html#AbdiR21
https://ui.adsabs.harvard.edu/abs/2020arXiv200405220A/abstract
https://doi.org/10.1109/TCOMM.2021.3056679
https://ieeexplore.ieee.org/document/9345722
http://urn.fi/URN:NBN:fi:jyu-202105253186

Sparse Code Multiple Access: Potentials and Challenges

Autoren: Rebhi, Manel Hassan, Kais Raoof, Kosai et al.

Weitere Verfasser: Rebhi, Manel Hassan, Kais Raoof, Kosai et al.

Quelle: IEEE Open Journal of the Communications Society, Vol 2, Pp 1205-1238 (2021)

Schlagwörter: [INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI], code-domain, codebook design, NOMA, TK5101-6720, 02 engineering and technology, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], SCMA, multi-dimensional constellations, Telecommunication, 0202 electrical engineering, electronic engineering, information engineering, message-passing algorithms, Transportation and communications, HE1-9990

Zugangs-URL: https://ieeexplore.ieee.org/ielx7/8782661/9309127/09432947.pdf
https://doaj.org/article/40a79eba2a734c5ea831af3b747562a5
https://ieeexplore.ieee.org/document/9432947
https://hal.science/hal-03688586v1
https://doi.org/10.1109/ojcoms.2021.3081166

Optimal deployment of resources for maximizing impact in spreading processes

Autoren: Lokhov, Andrey Y. Saad, David

Quelle: Proceedings of the National Academy of Sciences of the United States of America, 2017 Sep . 114(39), E8138-E8146.

Zugangs-URL: https://www.jstor.org/stable/26488057

Universality laws for Gaussian mixtures in generalized linear models*: Universality laws for Gaussian mixtures in generalized linear models

Autoren: Dandi, Yatin Stephan, Ludovic Krzakala, Florent et al.

Quelle: Journal of Statistical Mechanics: Theory and Experiment. 2024:104015

Schlagwörter: FOS: Computer and information sciences, deep learning, Mathematics - Statistics Theory, Machine Learning (stat.ML), 02 engineering and technology, Statistics Theory (math.ST), 01 natural sciences, Statistical mechanics, structure of matter, network dynamics, learning theory, Statistics - Machine Learning, 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, FOS: Mathematics, message-passing algorithms

Dateibeschreibung: application/xml

Zugangs-URL: http://arxiv.org/abs/2302.08933
https://zbmath.org/7979315
https://doi.org/10.1088/1742-5468/ad65e7

Universally-Optimal Distributed Exact Min-Cut

Autoren: Ghaffari, Mohsen Zuzic, Goran

Quelle: PODC'22: Proceedings of the 2022 ACM Symposium on Principles of Distributed Computing

Schlagwörter: exact minimum cut, distributed algorithms, message-passing algorithms, CONGEST model, minor-aggregation model, low-congestion shortcuts, universal optimality

Zugangs-URL: http://hdl.handle.net/20.500.11850/563069

Probing the latent hierarchical structure of data via diffusion models

Autoren: Sclocchi, Antonio Favero, Alessandro Itzhak Levi, Noam et al.

Schlagwörter: correlation functions, critical behavior of disordered systems, deep learning, message-passing algorithms

Relation: Journal of Statistical Mechanics: Theory and Experiment; #PLACEHOLDER_PARENT_METADATA_VALUE#; 454953; https://infoscience.epfl.ch/handle/20.500.14299/253471

Verfügbarkeit: https://doi.org/10.1088/1742-5468/aded6c
https://infoscience.epfl.ch/handle/20.500.14299/253471
https://hdl.handle.net/20.500.14299/253471

Optimal Thresholds and Algorithms for a Model of Multi-modal Learning in High Dimensions

Autoren: Keup, Christian Zdeborova, Lenka

Schlagwörter: statistical inference, analysis of algorithms, machine learning, learning theory, message-passing algorithms, classical phase transitions

Relation: JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT; https://infoscience.epfl.ch/handle/20.500.14299/254723; WOS:001581767900001

Verfügbarkeit: https://doi.org/10.1088/1742-5468/ae0428
https://infoscience.epfl.ch/handle/20.500.14299/254723
https://hdl.handle.net/20.500.14299/254723

Phase Diagram of Compressed Sensing with l 0 -norm Regularization

Autoren: Barbier, Damien Lucibello, Carlo Saglietti, Luca et al.

Schlagwörter: message-passing algorithms, spin glasses, statistical inference, communication, supply and information networks

Relation: JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT; #PLACEHOLDER_PARENT_METADATA_VALUE#; CUP J53D23001330001; https://infoscience.epfl.ch/handle/20.500.14299/251669; WOS:001509814700001

Verfügbarkeit: https://doi.org/10.1088/1742-5468/adca21
https://infoscience.epfl.ch/handle/20.500.14299/251669
https://hdl.handle.net/20.500.14299/251669

Approximate message passing with spectral initialization for generalized linear models * * This article is an updated version of: Mondelli M and Venkataramanan R 2021 Approximate message passing with spectral initialization for generalized linear models Proc. 24th Int. Conf. Artificial Intelligence and Statistics vol 130, ed A Banerjee and K Fukumizu pp 397–405

Autoren: Mondelli, Marco Venkataramanan, Ramji DSpace at Cambridge pro (8.1)

Weitere Verfasser: Mondelli, Marco Venkataramanan, Ramji DSpace at Cambridge pro (8.1)

Schlagwörter: Paper, machine learning, learning theory, ML 2022, message-passing algorithms, statistical inference

Dateibeschreibung: text/xml; application/pdf

Large deviations in the perceptron model and consequences for active learning

Autoren: Cui, H Saglietti, L Zdeborová, L et al.

Weitere Verfasser: Cui, H Saglietti, L Zdeborová, L et al.

Quelle: EISSN: 2632-2153 ; Machine Learning: Science and Technology ; https://cea.hal.science/cea-04542510 ; Machine Learning: Science and Technology, 2021, 2 (4), pp.045001. ⟨10.1088/2632-2153/abfbbb⟩ ; https://iopscience.iop.org/article/10.1088/2632-2153/abfbbb

Schlagwörter: Disordered Systems and Neural Networks (cond-mat.dis-nn), Machine Learning (cs.LG), Active learning Large Deviations Perceptron Model Message-passing algorithms, Active learning, Large Deviations, Perceptron Model, Message-passing algorithms, [PHYS]Physics [physics]

Relation: info:eu-repo/grantAgreement//714608/EU/Statistical Mechanics of Learning/SMILE

Verfügbarkeit: https://cea.hal.science/cea-04542510
https://cea.hal.science/cea-04542510v1/document
https://cea.hal.science/cea-04542510v1/file/1912.03927.pdf
https://doi.org/10.1088/2632-2153/abfbbb