Search Results - "memory-based algorithms"

Shared Memory-based Algorithms for MPI Irregular Collective Operations

Authors: Alexey Romanyuta Mikhail Kurnosov

Source: 2022 IEEE International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON). :1-4

Shared Memory-based Algorithms for Vector Collective Operations of the MPI Standard

Authors: A. A. Romanyuta M. G. Kurnosov

Source: The Herald of the Siberian State University of Telecommunications and Informatics. :38-47

How can we predict transportation stock prices using artificial intelligence? Findings from experiments with Long Short-Term Memory based algorithms

Authors: Dinar Ajeng Kristiyanti Willibrordus Bayu Nova Pramudya Samuel Ady Sanjaya

Source: International Journal of Information Management Data Insights, Vol 4, Iss 2, Pp 100293- (2024)

Subject Terms: Activation, Long short-term memory, Optimizer, Prediction, Transportation stock, Information technology, T58.5-58.64

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S266709682400082X; https://doaj.org/toc/2667-0968

Access URL: https://doaj.org/article/c8a8a4b97a2a493cb4e597677e4b8b92

Memory-Based Algorithms for Abrupt Change Detection in Sensor Data Streams

Authors: D. Nikovski Ankur Jain

Source: 2007 5th IEEE International Conference on Industrial Informatics. :547-552

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 0101 mathematics, 01 natural sciences

Access URL: http://www.merl.com/publications/docs/TR2007-024.pdf
http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4384816
https://www.merl.com/publications/docs/TR2007-024.pdf
http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000004384816
http://ieeexplore.ieee.org/document/4384816/
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4384816

Predicting Hydromodification in Streams Using Nonlinear Memory-Based Algorithms in Southern California Streams

Authors: Ashmita Sengupta Robert J. Hawley Eric D. Stein

Source: Journal of Water Resources Planning and Management. 144

Subject Terms: 13. Climate action, 0207 environmental engineering, 14. Life underwater, 02 engineering and technology, 15. Life on land, 6. Clean water

Access URL: https://www.cabdirect.org/cabdirect/abstract/20183170906?q=(similar%3a20103320698)
https://ascelibrary.org/doi/10.1061/%28ASCE%29WR.1943-5452.0000853

Main Memory-Based Algorithms for Efficient Parallel Aggregation for Temporal Databases

Authors: Jose Alvin G. Gendrano Jim M. Rodrigue Dengfeng Gao et al.

Source: Distributed and Parallel Databases. 16:123-163

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://arizona.pure.elsevier.com/en/publications/main-memory-based-algorithms-for-efficient-parallel-aggregation-f
https://doi.org/10.1023/B:DAPD.0000028553.70337.e1
https://www.cs.arizona.edu/~bkmoon/papers/dapd-gtdm.pdf
https://link.springer.com/article/10.1023/B:DAPD.0000028553.70337.e1
https://www.cs.arizona.edu/people/bkmoon/papers/dapd-gtdm.pdf
http://www.cs.arizona.edu/people/rts/pubs/DPD04.pdf

How can we predict transportation stock prices using artificial intelligence? Findings from experiments with Long Short-Term Memory based algorithms

Authors: Kristiyanti, Dinar Ajeng Pramudya, Willibrordus Bayu Nova Sanjaya, Samuel Ady

Subject Terms: 005.2 Programming for Specific Computers, Algorithm, HTML, PHP, java, C++, 006.3 Artificial Intelligence, Machine Learning, Pattern Recognition, Data Mining

File Description: text

Relation: https://kc.umn.ac.id/id/eprint/35186/1/ct_transportation_stock_prices_using_artificial_intelligence.pdf; Kristiyanti, Dinar Ajeng and Pramudya, Willibrordus Bayu Nova and Sanjaya, Samuel Ady (2024) How can we predict transportation stock prices using artificial intelligence? Findings from experiments with Long Short-Term Memory based algorithms. International Journal of Information Management Data Insights, 4 (2). pp. 1-17. ISSN 26670968

Availability: https://kc.umn.ac.id/id/eprint/35186/
https://kc.umn.ac.id/id/eprint/35186/1/ct_transportation_stock_prices_using_artificial_intelligence.pdf
https://www.sciencedirect.com/science/article/pii/S266709682400082X

Main memory-based algorithms for efficient parallel aggregation for temporal databases, Distributed and Parallel Databases

Authors: Dengfeng Gao Jose Alvin G. Gendrano et al.

Contributors: Dengfeng Gao Jose Alvin G. Gendrano et al.

Source: http://www.cs.arizona.edu/~rts/pubs/DPD04.pdf.

Subject Terms: aggregation tree algorithm, cost model, data reduction, parallel temporal aggregation, result placement, temporal

File Description: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.95.3436; http://www.cs.arizona.edu/~rts/pubs/DPD04.pdf

Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.95.3436
http://www.cs.arizona.edu/~rts/pubs/DPD04.pdf

Comparative Study of Nature-Inspired Algorithms

Authors: Tahir, Mohammad, Abdullah Khan, Hasan, Faraz Khan, Mohammad, Mohsin et al.

Contributors: Tahir, Mohammad, Abdullah Khan, Hasan, Faraz Khan, Mohammad, Mohsin et al.

Source: IFIP Advances in Information and Communication Technology ; International Working Conference on Transfer and Diffusion of IT (TDIT) ; https://inria.hal.science/hal-03701777 ; International Working Conference on Transfer and Diffusion of IT (TDIT), Dec 2020, Tiruchirappalli, India. pp.353-361, ⟨10.1007/978-3-030-64849-7_32⟩

Subject Terms: Nature-inspired algorithms, Stochastic algorithms, Deterministic algorithms, Memory based algorithms, Memory-less algorithms, [INFO]Computer Science [cs], [SHS.INFO]Humanities and Social Sciences/Library and information sciences

Subject Geographic: Tiruchirappalli, India

Availability: https://inria.hal.science/hal-03701777
https://inria.hal.science/hal-03701777v1/document
https://inria.hal.science/hal-03701777v1/file/497052_1_En_32_Chapter.pdf
https://doi.org/10.1007/978-3-030-64849-7_32

Main memory-based algorithms for efficient parallel aggregation for temporal databases

Authors: Gao, Dengfeng Gendrano, Jose Alvin G. Moon, Bongki et al.

Source: Faculty Research Work

Subject Terms: Temporal databases, Parallel algorithms, Computer Sciences

Relation: https://animorepository.dlsu.edu.ph/faculty_research/6352

Availability: https://animorepository.dlsu.edu.ph/faculty_research/6352

Main Memory-Based Algorithms for Efficient Parallel Aggregation for Temporal Databases.

Authors: Dengfeng Gao Gendrano, Jose Alvin G. Bongki Moon et al.

Source: Distributed & Parallel Databases; Sep2004, Vol. 16 Issue 2, p123-163, 41p, 6 Diagrams, 16 Charts, 25 Graphs

Subject Terms: TEMPORAL databases, ALGORITHMS, DATA reduction, DATABASE management, MANAGEMENT information systems

Memory-Assisted Dynamic Multi-Objective Evolutionary Algorithm for Feature Drift Problem

Contributors: Sahmoud, Shaaban Topcuoglu, Haluk Rahmi

Subject Terms: dynamic multi-objective evolutionary algorithms, learning in non-stationary environments, severity of changes, feature drift, memory-based algorithms, FEATURE-SELECTION, OPTIMIZATION

Relation: 2020 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC); IEEE Congress on Evolutionary Computation; https://hdl.handle.net/11424/226409; WOS:000703998201116

Availability: https://hdl.handle.net/11424/226409

Memory-Assisted Dynamic Multi-Objective Evolutionary Algorithm for Feature Drift Problem

Contributors: Sahmoud S., Topcuoglu H.R.

Subject Terms: dynamic multi-objective evolutionary algorithms, feature drift, learning in non-stationary environments, memory-based algorithms, severity of changes

Relation: 2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings; https://hdl.handle.net/11424/248120

Availability: https://hdl.handle.net/11424/248120
https://doi.org/10.1109/CEC48606.2020.9185730

Memory-Based Algorithms for Abrupt Change Detection in Sensor Data Streams.

Authors: Nikovski, D. Jain, A.

Source: 2007 5th IEEE International Conference on Industrial Informatics; 2007, p547-552, 6p

Memory-Based Optimization Methods for Model-Agnostic Meta-Learning and Personalized Federated Learning.

Authors: Bokun Wang Zhuoning Yuan Yiming Ying et al.

Source: Journal of Machine Learning Research. 2023, Vol. 24, p1-46. 46p.

Subject Terms: *MATHEMATICAL optimization, *ALGORITHMS, FEDERATED learning, INDIVIDUALIZED instruction, ITERATIVE learning control

Memory-Based Weighted-Majority Prediction For Recommender Systems

Authors: Joaquin Delgado Naohiro Ishii The Pennsylvania State University CiteSeerX Archives

Contributors: Joaquin Delgado Naohiro Ishii The Pennsylvania State University CiteSeerX Archives

Source: http://www-ishii.ics.nitech.ac.jp/~jdelgado/acm_sigir.pdf.

Subject Terms: On-line learning, Memory-based algorithms, Collaborative Filtering, User Modeling

File Description: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.40.7269

Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.40.7269
http://www-ishii.ics.nitech.ac.jp/~jdelgado/acm_sigir.pdf

Comparative Study on Influences of False Negative Ratings in Collaborative Filtering with Fuzzy Co-Clustering.

Authors: Honda, Katsuhiro Lee, Jun-Seo Ubukata, Seiki et al.

Source: Procedia Computer Science. 2025, Vol. 270, p476-484. 9p.

Subject Terms: Recommender systems, Fuzzy clustering technique, False positive error, Mathematical optimization, Mathematical models, Information filtering, Consumer preferences

Predicting Hydromodification in Streams Using Nonlinear Memory-Based Algorithms in Southern California Streams.

Authors: Sengupta, Ashmita Hawley, Robert J. Stein, Eric D.

Source: Journal of Water Resources Planning & Management; Jan2018, Vol. 144 Issue 1, pN.PAG-N.PAG, 1p

Subject Terms: RIVER channels, ARTIFICIAL neural networks, SUPPORT vector machines, ARID regions, RIPARIAN areas

Geographic Terms: SOUTHERN California

Business Informatics ; Products and services recommendation systems in e-commerce. Recommendation methods, algorithms, and measures of their effectiveness

Authors: Lasek, Mirosława Kosieradzki, Dominik

Source: Uniwersytet Ekonomiczny we Wrocławiu

Subject Terms: recommendation systems, recommender systems, recommendation methods, recommendation algorithms, collaborative filtering, content-based filtering, memory-based algorithms, model-based algorithms, predictive accuracy metrics, classification accuracy metrics, rank accuracy metrics, systemy rekomendacji w handlu elektronicznym, metody i algorytmy rekomendacyjne, miary oceny skuteczności rekomendacji

File Description: application/pdf

Relation: Informatyka Ekonomiczna = Business Informatics, 2014, Nr 1 (31); oai:dbc.wroc.pl:publication:27839; https://dbc.wroc.pl/dlibra/publication/edition/25202/content; oai:dbc.wroc.pl:25202

Availability: https://dbc.wroc.pl/dlibra/publication/edition/25202/content

Systemy rekomendacji produktów i usług eCommerce Zalecanie metod, rzeczy, i środków ich) Economic Computer Science = Business Informatics, 2014, No. 1 (31), p. 304-317
Products and services recommendation systems in e-commerce. Recommendation methods, algorithms, and measures of their effectiveness. Informatyka Ekonomiczna = Business Informatics, 2014, Nr 1 (31), s. 304-317

Authors: Kosieradzki, Dominik Lasek, Mirosław Lasek, Mirosława

Availability: http://data.europeana.eu/aggregation/europeana/0940420/_nn32xk8
http://data.europeana.eu/item/0940420/_nn32xk8