Konstantinos Sechidis
Title
Cited by
Cited by
Year
On the stratification of multi-label data
K Sechidis, G Tsoumakas, I Vlahavas
Machine Learning and Knowledge Discovery in Databases, 145-158, 2011
1962011
On the Stability of Feature Selection Algorithms
S Nogueira, K Sechidis, G Brown
Journal of Machine Learning Research 18, 1-54, 2018
682018
Distinguishing prognostic and predictive biomarkers: an information theoretic approach
K Sechidis, K Papangelou, PD Metcalfe, D Svensson, J Weatherall, ...
Bioinformatics 34 (19), 3365-3376, 2018
282018
Simple strategies for semi-supervised feature selection
K Sechidis, G Brown
Machine Learning 107 (2), 357-395, 2018
192018
Information theoretic feature selection in multi-label data through composite likelihood
K Sechidis, N Nikolaou, G Brown
Statistical Techniques in Pattern Recognition (SPR) and Structural and …, 2014
192014
Statistical Hypothesis Testing in Positive Unlabelled Data
K Sechidis, B Calvo, G Brown
Machine Learning and Knowledge Discovery in Databases, 66-81, 2014
182014
Dealing with under-reported variables: An information theoretic solution
K Sechidis, M Sperrin, ES Petherick, M Luján, G Brown
International Journal of Approximate Reasoning 85, 159-177, 2017
122017
Exploring the consequences of distributed feature selection in DNA microarray data
V Bolón-Canedo, K Sechidis, N Sánchez-Marono, A Alonso-Betanzos, ...
International Joint Conference on Neural Networks (IJCNN), 2017
122017
Markov blanket discovery in positive-unlabelled and semi-supervised data
K Sechidis, G Brown
Machine Learning and Knowledge Discovery in Databases, 351-366, 2015
102015
Algorithmic challenges in Big Data analytics
V Bolón-Canedo, B Remeseiro, K Sechidis, D Martinez-Rego, ...
European Symposium on Artificial Neural Networks, Computational Intelligence …, 2017
92017
On the Use of Spearman’s Rho to Measure the Stability of Feature Rankings
S Nogueira, K Sechidis, G Brown
Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA), 2017
92017
Efficient feature selection using shrinkage estimators
K Sechidis, L Azzimonti, A Pocock, G Corani, J Weatherall, G Brown
Machine Learning 108 (8), 1261-1286, 2019
82019
Toward an Understanding of Adversarial Examples in Clinical Trials
K Papangelou, K Sechidis, J Weatherall, G Brown
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2018
82018
Hypothesis testing and feature selection in semi-supervised data
K Sechidis
University of Manchester, 2015
52015
Information theoretic multi-target feature selection via output space quantization
K Sechidis, E Spyromitros-Xioufis, I Vlahavas
Entropy 21 (9), 855, 2019
42019
Feature selection with limited bit depth mutual information for portable embedded systems
L Morán-Fernández, K Sechidis, V Bolón-Canedo, A Alonso-Betanzos, ...
Knowledge-Based Systems 197, 105885, 2020
32020
Insights into distributed feature ranking
V Bolón-Canedo, K Sechidis, N Sánchez-Maroño, A Alonso-Betanzos, ...
Information Sciences 496, 378-398, 2019
32019
Multi-target regression via output space quantization
E Spyromitros-Xioufis, K Sechidis, I Vlahavas
International Joint Conference on Neural Networks (IJCNN), 2020
12020
On The Stability of Feature Selection in the Presence of Feature Correlations
K Sechidis, K Papangelou, S Nogueira, J Weatherall, G Brown
European Conference on Machine Learning and Principles and Practice of …, 2019
12019
Multi-target feature selection through output space clustering
K Sechidis, E Spyromitros-Xioufis, I Vlahavas
European Symposium on Artificial Neural Networks, Computational Intelligence …, 2019
12019
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Articles 1–20