Suchergebnisse - "active learning algorithm"

Swarm Intelligence-Based Functional Link Fuzzy Neural Estimator for Software Development Effort Estimation

Autoren: Benala, Tirimula Rao Kaushik, Anupama Dehuri, Satchidananda

Quelle: Journal of Electronics, Electromedical Engineering, and Medical Informatics; Vol 7 No 2 (2025): April; 253-269 ; 2656-8632 ; 10.35882/jeeemi.v7i2

Schlagwörter: Software Cost Estimation, Functional Link Artificial Neural Network, Fuzzy Logic System, Interval Type-2FLS, Particle Swarm Optimization, Active Learning Algorithm

Dateibeschreibung: application/pdf

Relation: http://jeeemi.org/index.php/jeeemi/article/view/492/220; http://jeeemi.org/index.php/jeeemi/article/view/492

Verfügbarkeit: http://jeeemi.org/index.php/jeeemi/article/view/492
https://doi.org/10.35882/jeeemi.v7i2.492

Probabilistic analysis of dynamic stability for a rotating BDFG tapered beam with time-varying velocity and stochastic parameters

Autoren: Yanxun Zhou Yimin Zhang Guo Yao

Quelle: Acta Mechanica. 232:1709-1728

Schlagwörter: Hamilton principle, Inhomogeneity in solid mechanics, Numerical approximation of solutions of dynamical problems in solid mechanics, Learning and adaptive systems in artificial intelligence, functionally graded material, 02 engineering and technology, active learning algorithm, 0201 civil engineering, Kriging-based system reliability method, parametric excitation, Bolotin method, 0203 mechanical engineering, Stochastic and other probabilistic methods applied to problems in solid mechanics, Rods (beams, columns, shafts, arches, rings, etc.), Stability of dynamical problems in solid mechanics

Dateibeschreibung: application/xml

Zugangs-URL: https://link.springer.com/content/pdf/10.1007/s00707-020-02931-0.pdf

Online Multitask Relative Similarity Learning

Autoren: HAO, Shuji ZHAO, Peilin LIU, Yong et al.

Quelle: Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence. :1823-1829

Schlagwörter: Online learning algorithms, Artificial intelligence, Specific tasks, Artificial Intelligence and Robotics, Databases and Information Systems, Theoretical guarantees, Theory and Algorithms, Active-learning algorithm, Real-world datasets, 02 engineering and technology, Learning algorithms, E-learning, Similarity functions, Similarity learning, 0202 electrical engineering, electronic engineering, information engineering, Learning approach

Dateibeschreibung: application/pdf

Zugangs-URL: https://www.ijcai.org/proceedings/2017/0253.pdf
https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=4848&context=sis_research
http://oar.a-star.edu.sg/jspui/bitstream/123456789/2161/1/ijcai_0253.pdf
https://dblp.uni-trier.de/db/conf/ijcai/ijcai2017.html#HaoZLHM17
https://ink.library.smu.edu.sg/sis_research/3846/
https://core.ac.uk/display/132698496
https://www.ijcai.org/Proceedings/2017/253

Advancing anomaly detection in computational workflows with active learning

Autoren: Raghavan, Krishnan Papadimitriou, George Jin, Hongwei et al.

Quelle: Future Generation Computer Systems

Schlagwörter: learning experience, training data, learning approach, detection of anomalies, workflow management system, problem, machine learning models, circumstances, data generation, environment, training purposes, applications, active learning, accurate model, volume, degradation, training, chemistry, campaign, physics, trace, science, model, large-scale experiments, action, task, active learning algorithm, data, accuracy, end-to-end

Relation: https://cdr.lib.unc.edu/downloads/hx11xv772?file=thumbnail; https://cdr.lib.unc.edu/downloads/hx11xv772

Verfügbarkeit: https://doi.org/10.17615/rtk6-4q54
https://cdr.lib.unc.edu/downloads/hx11xv772?file=thumbnail
https://cdr.lib.unc.edu/downloads/hx11xv772

Active learning combining uncertainty and diversity for multi‐class image classification

Autoren: Yingjie Gu Steve C. Chiu Zhong Jin

Quelle: IET Computer Vision, Vol 9, Iss 3, Pp 400-407 (2015)

Schlagwörter: QA76.75-76.765, multiclass image classification, Computer applications to medicine. Medical informatics, R858-859.7, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, support vector machine, Computer software, 02 engineering and technology, unlabelled data, pattern recognition applications, computer vision, active learning algorithm

Zugangs-URL: https://doaj.org/article/4f471b28669f4f3888830b16a4e8f3c7
https://dblp.uni-trier.de/db/journals/iet-cvi/iet-cvi9.html#GuJC15
https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2014.0140
https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-cvi.2014.0140
https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/iet-cvi.2014.0140

Parallel Active Learning: Eliminating Wait Time with Minimal Staleness

Autoren: Felt, Paul Haertel, Robbie Ringger, Eric K. et al.

Quelle: Faculty Publications

Schlagwörter: active learning algorithm, scores, parameterless method, Computer Sciences

Dateibeschreibung: application/pdf

Relation: https://scholarsarchive.byu.edu/facpub/100; https://scholarsarchive.byu.edu/context/facpub/article/1099/viewcontent/IR_CISOPTR_1288.pdf

Verfügbarkeit: https://scholarsarchive.byu.edu/facpub/100
https://scholarsarchive.byu.edu/context/facpub/article/1099/viewcontent/IR_CISOPTR_1288.pdf