Another Approach to Factoring by Continued Fractions

Authors: Turgut Hanoymak, Cihan Kayak

Source: Volume: 17, Issue: 133-46
Turkish Journal of Mathematics and Computer Science

Subject Terms: Factorization algorithms, continued fractions, RSA algorithm, cryptography, Cryptography, Kriptografi

File Description: application/pdf

Access URL: https://dergipark.org.tr/tr/pub/tjmcs/issue/92235/1569163

Computing LZ78-Derivates with Suffix Trees

Authors: Koppl, Dominik

Source: 2024 Data Compression Conference (DCC) DCC Data Compression Conference (DCC), 2024. :133-142 Mar, 2024

Relation: 2024 Data Compression Conference (DCC)

Computing Lexicographic Parsings

Authors: Koppl, Dominik

Source: 2022 Data Compression Conference (DCC) DCC Data Compression Conference (DCC), 2022. :232-241 Mar, 2022

Relation: 2022 Data Compression Conference (DCC)

Substring compression variations and LZ78-Derivates

Authors: Köppl, Dominik

Source: In Information Systems August-September 2025 133

Development of Large Numbers Factorization Algorithm

Authors: Illiashenko, Oleg, Pevnev, Vladimir

Source: 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), 2019 10th IEEE International Conference on. 2:1078-1081 Sep, 2019

Relation: 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)

Framework for evaluation and comparison of integer factorization algorithms

Authors: Duta, Cristina-Loredana, Gheorghe, Laura, Tapus, Nicolae

Source: 2016 SAI Computing Conference (SAI) SAI Computing Conference (SAI), 2016. :1047-1053 Jul, 2016

Relation: 2016 SAI Computing Conference (SAI)

Contextual-Aware Hybrid Recommender System for Mixed Cold-Start Problems in Privacy Protection

Authors: Zhao, Vicky Na, Moh, Melody, Moh, Teng-Sheng

Source: 2016 IEEE 2nd International Conference on Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing (HPSC), and IEEE International Conference on Intelligent Data and Security (IDS) Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing (HPSC), and IEEE International Conference on Intelligent Data and Security (IDS), 2016 IEEE 2nd International Conference on. :400-405 Apr, 2016

Relation: 2016 IEEE 2nd International Conference on Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing (HPSC) and IEEE International Conference on Intelligent Data and Security (IDS)

Adaptive antenna selection by parallel QR-factorization for cognitive radio cloud network

Authors: Chang, Shih Yu, Wu, Hsiao-Chun

Source: 2014 IEEE Global Communications Conference Global Communications Conference (GLOBECOM), 2014 IEEE. :882-887 Dec, 2014

Relation: GLOBECOM 2014 - 2014 IEEE Global Communications Conference

Images fusion based on a Coupled Nonnegative Tensors Factorization approach (CNTF), application to OLCI and ETM sensors

Authors: Sylla, Diogone, Royer, Jean-Philip, Minghelli-Roman, Audrey, Thirion-Moreau, Nadelge, Mangin, Antoine

Source: 2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS) Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2013 5th Workshop on. :1-4 Jun, 2013

Relation: 2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)

Revisiting the GreCon algorithm for Boolean matrix factorization

Authors: Trnecka, Martin, Vyjidacek, Roman ^⁎

Source: In Knowledge-Based Systems 5 August 2022 249

Symbolic Computation Applied to the Study of the Kernel of Special Classes of Paired Singular Integral Operators

Authors: Conceição, Ana C.

Contributors: Sapientia

Source: Mathematics in Computer Science. 15:63-90

Subject Terms: Symbolic computation, Sistema de álgebra computacional, Kernel of paired singular integral operators, Factorization algorithms, Essentially bounded matrix functions, 0101 mathematics, Wolfram Mathematica, 01 natural sciences

File Description: application/pdf

Access URL: https://sapientia.ualg.pt/bitstream/10400.1/14645/1/Conceicao_MCS_2020_revised.pdf
https://dblp.uni-trier.de/db/journals/mics/mics15.html#Conceicao21
https://link.springer.com/article/10.1007/s11786-020-00463-3
https://hdl.handle.net/10400.1/14645

Quantum Approach Explains the Need for Expert Knowledge: On the Example of Econometrics

Authors: Sriboonchitta, Songsak^Aff4, Nguyen, Hung T.^{Aff4, Aff5}, Kosheleva, Olga^Aff6, Kreinovich, Vladik^Aff6, Nguyen, Thach Ngoc^Aff7

Contributors: Kacprzyk, Janusz, Series Editor^Aff1, Kreinovich, Vladik, editor^Aff2, Sriboonchitta, Songsak, editor^Aff3

Source: Structural Changes and their Econometric Modeling. 808:191-199

Batched matrix computations on hardware accelerators based on GPUs

Contributors: Dongarra, Jack [Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Univ. of Manchester (United Kingdom)]

Source: International Journal of High Performance Computing Applications; 29; 2

File Description: Medium: ED; Size: p. 193-208

Access URL: http://www.osti.gov/scitech/servlets/purl/1361289

Optimizing the SVD Bidiagonalization Process for a Batch of Small Matrices

Authors: Jack Dongarra, Tingxing Dong, Stanimire Tomov, Azzam Haidar

Source: Dong, T, Haidar, A, Tomov, S & Dongarra, J 2017, Optimizing the SVD Bidiagonalization Process for a Batch of Small Matrices. in Procedia Computer Science. vol. 108, pp. 1008-1018. https://doi.org/10.1016/j.procs.2017.05.237

Subject Terms: two-sided factorization algorithms, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Hardware accelerators, 0101 mathematics, batched, Singular Value Problems, 01 natural sciences

File Description: application/pdf

Access URL: https://research.manchester.ac.uk/en/publications/d652df67-1aa0-4b67-b45c-8b7f9db562d6
https://doi.org/10.1016/j.procs.2017.05.237
https://www.sciencedirect.com/science/article/pii/S1877050917308645
https://www.icl.utk.edu/publications/optimizing-svd-bidiagonalization-process-batch-small-matrices
https://www.icl.utk.edu/files/publications/2017/icl-utk-953-2017.pdf
https://www.research.manchester.ac.uk/portal/files/57088796/optimizing_the_svd.pdf
https://core.ac.uk/display/83923148
https://www.sciencedirect.com/science/article/abs/pii/S1877050917308645
https://research.manchester.ac.uk/en/publications/d652df67-1aa0-4b67-b45c-8b7f9db562d6
https://pure.manchester.ac.uk/ws/files/57088796/optimizing_the_svd.pdf
https://doi.org/10.1016/j.procs.2017.05.237

Accelerating the SVD bi-diagonalization of a batch of small matrices using GPUs

Authors: Tingxing Dong, Azzam Haidar, Jack Dongarra, Stanimire Tomov

Source: Dong, T, Haidar, A, Tomov, S & Dongarra, J 2018, 'Accelerating the SVD Bidiagonalization of a Batch of Small Matrices using GPUs', Journal of Computational Science, vol. 26, pp. 237-245. https://doi.org/10.1016/j.jocs.2018.01.007

Subject Terms: Batched, Numerical linear algebra, 0202 electrical engineering, electronic engineering, information engineering, Two-sided factorization algorithms, 02 engineering and technology, Hardware accelerators, Eigenvalue and singular value problems

File Description: application/pdf

Access URL: https://www.research.manchester.ac.uk/portal/files/65822562/1_s2.0_S187775031731150X_main.pdf
https://www.research.manchester.ac.uk/portal/files/65822562/1_s2.0_S187775031731150X_main.pdf
https://www.sciencedirect.com/science/article/pii/S187775031731150X#!
https://www.research.manchester.ac.uk/portal/en/publications/accelerating-the-svd-bidiagonalization-of-a-batch-of-small-matrices-using-gpus(52d77474-7ce1-47eb-9ae2-c010a09f2355).html
https://www.sciencedirect.com/science/article/pii/S187775031731150X
https://doi.org/10.1016/j.jocs.2018.01.007
https://www.icl.utk.edu/publications/accelerating-svd-bi-diagonalization-batch-small-matrices-using-gpus

High-performance Cholesky factorization for GPU-only execution

Authors: Haidar, Azzam, Abdelfatah, Ahmad, Tomov, Stanimire, Dongarra, Jack

Source: Proceedings of the General Purpose GPUs. :42-52

Availability: http://dl.acm.org/doi/10.1145/3038228.3038237

Optimization for performance and energy for batched matrix computations on GPUs

Authors: Haidar, Azzam, Dong, Tingxing, Luszczek, Piotr, Tomov, Stanimire, Dongarra, Jack

Source: Proceedings of the 8th Workshop on General Purpose Processing using GPUs. :59-69

Availability: http://dl.acm.org/doi/10.1145/2716282.2716288

RETRACTED: Batched matrix computations on hardware accelerators based on GPUs

Authors: Haidar, Azzam, Dong, Tingxing, Luszczek, Piotr, Tomov, Stanimire, Dongarra, Jack

Source: Haidar, A, Dong, T, Luszczek, P, Tomov, S & Dongarra, J 2015, 'Batched matrix computations on hardware accelerators based on GPUs', International Journal of High Performance Computing Applications, vol. 29, no. 2, pp. 193-208. https://doi.org/10.1177/1094342014567546

Subject Terms: one-sided factorization algorithms, numerical linear algebra, 0202 electrical engineering, electronic engineering, information engineering, Batched factorization, 02 engineering and technology, numerical software libraries, hardware accelerators, 7. Clean energy

Access URL: https://www.osti.gov/biblio/1361289
https://research.manchester.ac.uk/en/publications/3b928883-2575-424b-9c5c-93c76c117dd7
https://doi.org/10.1177/1094342014567546
https://research.manchester.ac.uk/en/publications/3b928883-2575-424b-9c5c-93c76c117dd7
https://doi.org/10.1177/1094342014567546
http://www.scopus.com/inward/record.url?scp=84930795358&partnerID=8YFLogxK

On factorization of multivariate polynomials over algebraic number and function fields

Authors: Javadi, Seyed Mohammad Mahdi, Monagan, Michael B.

Source: Proceedings of the 2009 international symposium on Symbolic and algebraic computation. :199-206

Availability: http://dl.acm.org/doi/10.1145/1576702.1576731

A SEMG-Force Estimation Framework Based on a Fast Orthogonal Search Method Coupled with Factorization Algorithms

Authors: Chen, Xiang, Yuan, Yuan, Cao, Shuai, Zhang, Xu, Chen, Xun

Subject Terms: High-density SEMG, Factorization algorithms, Fast orthogonal search, Muscle force estimation

Relation: Sensors 18 (7): 2238 (2018); http://hdl.handle.net/2429/70748

Availability: http://hdl.handle.net/2429/70748
https://doi.org/10.3390/s18072238