Jafar Tanha
Jafar Tanha
University of Amsterdam
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Cited by
Cited by
Semi-supervised self-training for decision tree classifiers
J Tanha, M Van Someren, H Afsarmanesh
International Journal of Machine Learning and Cybernetics 8, 355-370, 2017
Boosting methods for multi-class imbalanced data classification: an experimental review
J Tanha, Y Abdi, N Samadi, N Razzaghi, M Asadpour
Journal of Big Data 7 (1), 1-47, 2020
The role of collaborative networks in sustainability
LM Camarinha-Matos, H Afsarmanesh, X Boucher
Collaborative Networks for a Sustainable World: 11th IFIP WG 5.5 Working …, 2010
COVID-19 infection forecasting based on deep learning in Iran
M Azarafza, M Azarafza, J Tanha
MedRxiv, 2020.05. 16.20104182, 2020
Tune your brown clustering, please
L Derczynski, S Chester, KS Bøgh
International Conference Recent Advances in Natural Language Processing …, 2015
Boosting for multiclass semi-supervised learning
J Tanha, M Van Someren, H Afsarmanesh
Pattern Recognition Letters 37, 63-77, 2014
Combination of ant colony optimization and Bayesian classification for feature selection in a bioinformatics dataset
MH Aghdam, J Tanha, AR Naghsh-Nilchi, ME Basiri
Journal of Computer Science & Systems Biology 2 (3), 186-199, 2009
Disagreement-based co-training
J Tanha, M van Someren, H Afsarmanesh
2011 IEEE 23rd international conference on tools with artificial …, 2011
Relationship among prognostic indices of breast cancer using classification techniques
J Tanha, H Salarabadi, M Aznab, A Farahi, M Zoberi
Informatics in Medicine Unlocked 18, 100265, 2020
Multiclass semi-supervised learning for animal behavior recognition from accelerometer data
J Tanha, M Van Someren, M de Bakker, W Bouteny, ...
2012 IEEE 24th International Conference on Tools with Artificial …, 2012
CPSSDS: conformal prediction for semi-supervised classification on data streams
J Tanha, N Samadi, Y Abdi, N Razzaghi-Asl
Information Sciences 584, 212-234, 2022
MSSBoost: A new multiclass boosting to semi-supervised learning
J Tanha
Neurocomputing 314, 251-266, 2018
An adaboost algorithm for multiclass semi-supervised learning
J Tanha, M van Someren, H Afsarmanesh
2012 IEEE 12th International Conference on Data Mining, 1116-1121, 2012
COVID‐19 Detection Using Deep Convolutional Neural Networks and Binary Differential Algorithm‐Based Feature Selection from X‐Ray Images
MS Iraji, MR Feizi-Derakhshi, J Tanha
Complexity 2021 (1), 9973277, 2021
STDS: self-training data streams for mining limited labeled data in non-stationary environment
S Khezri, J Tanha, A Ahmadi, A Sharifi
Applied Intelligence 50, 1448-1467, 2020
A novel semi-supervised ensemble algorithm using a performance-based selection metric to non-stationary data streams
S Khezri, J Tanha, A Ahmadi, A Sharifi
Neurocomputing 442, 125-145, 2021
A selection metric for semi-supervised learning based on neighborhood construction
M Emadi, J Tanha, ME Shiri, MH Aghdam
Information Processing & Management 58 (2), 102444, 2021
A multiclass boosting algorithm to labeled and unlabeled data
J Tanha
International Journal of Machine Learning and Cybernetics 10 (12), 3647-3665, 2019
Ensemble approaches to semi-supervised learning
J Tanha
SIKS, 2013
AMTLDC: a new adversarial multi-source transfer learning framework to diagnosis of COVID-19
H Alhares, J Tanha, MA Balafar
Evolving Systems 14 (6), 1101-1115, 2023
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