Joaquim F. Pinto da Costa

According to our database1, Joaquim F. Pinto da Costa authored at least 17 papers between 2005 and 2019.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Bibliography

2019
Automatic Augmentation by Hill Climbing.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Deep Learning, 2019

Averse Deep Semantic Segmentation.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

2018
Binary ranking for ordinal class imbalance.
Pattern Anal. Appl., 2018

2017
Combining Ranking with Traditional Methods for Ordinal Class Imbalance.
Proceedings of the Advances in Computational Intelligence, 2017

Constraining Type II Error: Building Intentionally Biased Classifiers.
Proceedings of the Advances in Computational Intelligence, 2017

Ordinal Class Imbalance with Ranking.
Proceedings of the Pattern Recognition and Image Analysis - 8th Iberian Conference, 2017

2016
Tackling class imbalance with ranking.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

2014
Corrigendum to "The unimodal model for the classification of ordinal data" [Neural Networks 21 (2008) 78-79].
Neural Networks, 2014

2013
Multicriteria Models for Learning Ordinal Data: A Literature Review.
Proceedings of the Artificial Intelligence, Evolutionary Computing and Metaheuristics, 2013

2011
Weighted Correlation.
Proceedings of the International Encyclopedia of Statistical Science, 2011

A Weighted Principal Component Analysis and Its Application to Gene Expression Data.
IEEE/ACM Trans. Comput. Biology Bioinform., 2011

2010
An All-at-once Unimodal SVM Approach for Ordinal Classification.
Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

2008
The unimodal model for the classification of ordinal data.
Neural Networks, 2008

Breast contour detection with shape priors.
Proceedings of the International Conference on Image Processing, 2008

2007
Learning to Classify Ordinal Data: The Data Replication Method.
J. Mach. Learn. Res., 2007

2005
Modelling ordinal relations with SVMs: An application to objective aesthetic evaluation of breast cancer conservative treatment.
Neural Networks, 2005

Classification of Ordinal Data Using Neural Networks.
Proceedings of the Machine Learning: ECML 2005, 2005


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