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Jafar Tanha
Jafar Tanha
University of Amsterdam
Email confirmado em tabrizu.ac.ir - Página inicial
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Citado por
Citado por
Ano
Semi-supervised self-training for decision tree classifiers
J Tanha, M Van Someren, H Afsarmanesh
International Journal of Machine Learning and Cybernetics 8 (1), 355-370, 2017
2262017
The role of collaborative networks in sustainability
LM Camarinha-Matos, H Afsarmanesh, X Boucher
Working Conference on Virtual Enterprises, 1-16, 2010
922010
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
652020
COVID-19 infection forecasting based on deep learning in Iran
M Azarafza, M Azarafza, J Tanha
medRxiv, 2020
352020
Boosting for multiclass semi-supervised learning
J Tanha, M Van Someren, H Afsarmanesh
Pattern Recognition Letters 37, 63-77, 2014
302014
Tune your brown clustering, please
L Derczynski, S Chester, KS Bøgh
International Conference Recent Advances in Natural Language Processing …, 2015
272015
Disagreement-based co-training
J Tanha, M van Someren, H Afsarmanesh
2011 IEEE 23rd international conference on tools with artificial …, 2011
262011
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
252009
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
212012
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
172012
A multiclass boosting algorithm to labeled and unlabeled data
J Tanha
International Journal of Machine Learning and Cybernetics 10 (12), 3647-3665, 2019
132019
MSSBoost: A new multiclass boosting to semi-supervised learning
J Tanha
Neurocomputing 314, 251-266, 2018
132018
Ensemble approaches to semi-supervised learning
J Tanha
SIKS, 2013
132013
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
112020
Ensemble based co-training
J Tanha, M van Someren, H Afsarmanesh
23rd Benelux Conference on Artificial Intelligence, 223-231, 2011
72011
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
62021
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, 2021
62021
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 (5), 1448-1467, 2020
62020
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
52021
An intelligent sample selection approach to language model adaptation for hand-written text recognition
J Tanha, J de Does, K Depuydt
2014 14th International Conference on Frontiers in Handwriting Recognition …, 2014
52014
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