Spremljaj
Colin Bellinger
Naslov
Navedeno
Navedeno
Leto
A systematic review of data mining and machine learning for air pollution epidemiology
C Bellinger, MS Mohomed Jabbar, O Zaïane, A Osornio-Vargas
BMC public health 17, 1-19, 2017
3022017
Roadmap on machine learning in electronic structure
HJ Kulik, T Hammerschmidt, J Schmidt, S Botti, MAL Marques, M Boley, ...
Electronic Structure 4 (2), 023004, 2022
1532022
One-class versus binary classification: Which and when?
C Bellinger, S Sharma, N Japkowicz
2012 11th international conference on machine learning and applications 2 …, 2012
1332012
Synthetic oversampling with the majority class: A new perspective on handling extreme imbalance
S Sharma, C Bellinger, B Krawczyk, O Zaiane, N Japkowicz
2018 IEEE international conference on data mining (ICDM), 447-456, 2018
1192018
The class imbalance problem in deep learning
K Ghosh, C Bellinger, R Corizzo, P Branco, B Krawczyk, N Japkowicz
Machine Learning 113 (7), 4845-4901, 2024
992024
Smotefuna: Synthetic minority over-sampling technique based on furthest neighbour algorithm
AS Tarawneh, ABA Hassanat, K Almohammadi, D Chetverikov, ...
IEEE Access 8, 59069-59082, 2020
832020
Manifold-based synthetic oversampling with manifold conformance estimation
C Bellinger, C Drummond, N Japkowicz
Machine Learning 107, 605-637, 2018
692018
Framework for extreme imbalance classification: SWIM—sampling with the majority class
C Bellinger, S Sharma, N Japkowicz, OR Zaïane
Knowledge and Information Systems 62, 841-866, 2020
612020
Anomaly detection in gamma ray spectra: A machine learning perspective
S Sharma, C Bellinger, N Japkowicz, R Berg, K Ungar
2012 IEEE symposium on computational intelligence for security and defence …, 2012
502012
Understanding CNN fragility when learning with imbalanced data
D Dablain, KN Jacobson, C Bellinger, M Roberts, NV Chawla
Machine Learning 113 (7), 4785-4810, 2024
492024
Synthetic oversampling for advanced radioactive threat detection
C Bellinger, N Japkowicz, C Drummond
2015 IEEE 14th international conference on machine learning and applications …, 2015
442015
Beyond the boundaries of smote: A framework for manifold-based synthetically oversampling
C Bellinger, C Drummond, N Japkowicz
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2016
422016
Active learning for one-class classification
V Barnabé-Lortie, C Bellinger, N Japkowicz
2015 IEEE 14th international conference on machine learning and applications …, 2015
392015
Interdisciplinary-driven hypotheses on spatial associations of mixtures of industrial air pollutants with adverse birth outcomes
J Serrano-Lomelin, CC Nielsen, MSM Jabbar, O Wine, C Bellinger, ...
Environment international 131, 104972, 2019
302019
Sampling a longer life: Binary versus one-class classification revisited
C Bellinger, S Sharma, OR Zaıane, N Japkowicz
First International Workshop on Learning with Imbalanced Domains: Theory and …, 2017
302017
Undersampling with support vectors for multi-class imbalanced data classification
B Krawczyk, C Bellinger, R Corizzo, N Japkowicz
2021 International Joint Conference on Neural Networks (IJCNN), 1-7, 2021
292021
Active Measure Reinforcement Learning for Observation Cost Minimization.
C Bellinger, R Coles, M Crowley, I Tamblyn
Canadian AI, 2021
282021
Explainable image analysis for decision support in medical healthcare
R Corizzo, Y Dauphin, C Bellinger, E Zdravevski, N Japkowicz
2021 IEEE international conference on big data (big data), 4667-4674, 2021
242021
Remix: Calibrated resampling for class imbalance in deep learning
C Bellinger, R Corizzo, N Japkowicz
arXiv preprint arXiv:2012.02312, 2020
212020
RB-CCR: radial-based combined cleaning and resampling algorithm for imbalanced data classification
M Koziarski, C Bellinger, M Woźniak
Machine Learning 110, 3059-3093, 2021
202021
Sistem trenutno ne more izvesti postopka. Poskusite znova pozneje.
Članki 1–20