Konstantinos Sechidis

According to our database, Konstantinos Sechidis authored at least 26 papers between 2011 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

A machine learning perspective on the emotional content of Parkinsonian speech.

Konstantinos Sechidis, Riccardo Fusaroli, Juan Rafael Orozco-Arroyave, Detlef Wolf, Yan-Ping Zhang

Artif. Intell. Medicine, 2021

2020

Correction to: Efficient feature selection using shrinkage estimators.

Konstantinos Sechidis, Laura Azzimonti, Adam Craig Pocock, Giorgio Corani, James Weatherall, Gavin Brown

Mach. Learn., 2020

Feature selection with limited bit depth mutual information for portable embedded systems.

Laura Morán-Fernández, Konstantinos Sechidis, Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Gavin Brown

Knowl. Based Syst., 2020

Inferring Causal Direction from Observational Data: A Complexity Approach.

Nikolaos Nikolaou, Konstantinos Sechidis

CoRR, 2020

When Size Matters: Markov Blanket with Limited Bit Depth Conditional Mutual Information.

Laura Morán-Fernández, Eva Blanco-Mallo, Konstantinos Sechidis, Amparo Alonso-Betanzos, Verónica Bolón-Canedo

Proceedings of the IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning, 2020

Multi-target regression via output space quantization.

Eleftherios Spyromitros Xioufis, Konstantinos Sechidis, Ioannis P. Vlahavas

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019

Efficient feature selection using shrinkage estimators.

Konstantinos Sechidis, Laura Azzimonti, Adam Craig Pocock, Giorgio Corani, James Weatherall, Gavin Brown

Mach. Learn., 2019

Insights into distributed feature ranking.

Verónica Bolón-Canedo, Konstantinos Sechidis, Noelia Sánchez-Maroño, Amparo Alonso-Betanzos, Gavin Brown

Inf. Sci., 2019

Information Theoretic Multi-Target Feature Selection via Output Space Quantization.

Konstantinos Sechidis, Eleftherios Spyromitros Xioufis, Ioannis P. Vlahavas

Entropy, 2019

On the Stability of Feature Selection in the Presence of Feature Correlations.

Konstantinos Sechidis, Konstantinos Papangelou, Sarah Nogueira, James Weatherall, Gavin Brown

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Multi-target feature selection through output space clustering.

Konstantinos Sechidis, Eleftherios Spyromitros Xioufis, Ioannis P. Vlahavas

Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

2018

Simple strategies for semi-supervised feature selection.

Konstantinos Sechidis, Gavin Brown

Mach. Learn., 2018

Distinguishing prognostic and predictive biomarkers: an information theoretic approach.

Konstantinos Sechidis, Konstantinos Papangelou, Paul D. Metcalfe, David Svensson, James Weatherall, Gavin Brown

Bioinform., 2018

Toward an Understanding of Adversarial Examples in Clinical Trials.

Konstantinos Papangelou, Konstantinos Sechidis, James Weatherall, Gavin Brown

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

2017

On the Stability of Feature Selection Algorithms.

Sarah Nogueira, Konstantinos Sechidis, Gavin Brown

J. Mach. Learn. Res., 2017

Dealing with under-reported variables: An information theoretic solution.

Konstantinos Sechidis, Matthew Sperrin, Emily Petherick, Mikel Luján, Gavin Brown

Int. J. Approx. Reason., 2017

Exploring the consequences of distributed feature selection in DNA microarray data.

Verónica Bolón-Canedo, Konstantinos Sechidis, Noelia Sánchez-Maroño, Amparo Alonso-Betanzos, Gavin Brown

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

On the Use of Spearman's Rho to Measure the Stability of Feature Rankings.

Sarah Nogueira, Konstantinos Sechidis, Gavin Brown

Proceedings of the Pattern Recognition and Image Analysis - 8th Iberian Conference, 2017

Algorithmic challenges in big data analytics.

Verónica Bolón-Canedo, Beatriz Remeseiro, Konstantinos Sechidis, David Martínez-Rego, Amparo Alonso-Betanzos

Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

2016

Ranking Biomarkers Through Mutual Information.

Konstantinos Sechidis, Emily Turner, Paul D. Metcalfe, James Weatherall, Gavin Brown

CoRR, 2016

Estimating Mutual Information in Under-Reported Variables.

Konstantinos Sechidis, Matthew Sperrin, Emily Petherick, Gavin Brown

Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

2015

Markov Blanket Discovery in Positive-Unlabelled and Semi-supervised Data.

Konstantinos Sechidis, Gavin Brown

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

2014

Information Theoretic Feature Selection in Multi-label Data through Composite Likelihood.

Konstantinos Sechidis, Nikolaos Nikolaou, Gavin Brown

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2014

Statistical Hypothesis Testing in Positive Unlabelled Data.

Konstantinos Sechidis, Borja Calvo, Gavin Brown

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

2011

On the Stratification of Multi-label Data.

Konstantinos Sechidis, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

MLKD's Participation at the CLEF 2011 Photo Annotation and Concept-Based Retrieval Tasks.

Eleftherios Spyromitros Xioufis, Konstantinos Sechidis, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the CLEF 2011 Labs and Workshop, 2011