Publications

(2021). Using knockoffs for controlled predictive biomarker identification. Statistics in Medicine.

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(2021). A machine learning perspective on the emotional content of Parkinsonian speech. Artificial Intelligence in Medicine Volume 115, May 2021, 102061.

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(2020). When Size Matters: Markov Blanket with Limited Bit Depth Conditional Mutual Information. International Workshop on IoT, Edge, and Mobile for Embedded Machine Learning (ITEM).

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(2020). Feature selection with limited bit depth mutual information for portable embedded systems. Knowledge-Based Systems, volume 19, 105885.

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(2020). Multi-target regression via output space quantization. International Joint Conference on Neural Networks (IJCNN).

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(2019). Efficient feature selection using shrinkage estimators. Machine Learning Journal (MLJ), volume 108(8-9), pages 1261–1286.

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(2019). On the Stability of Feature Selection in the Presence of Feature Correlations. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML/PKDD). Acceptance rate 130/734 (18%).

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(2019). Information Theoretic Multi-Target Feature Selection via Output Space Quantization. Entropy, volume 21(9).

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(2019). Insights into distributed feature ranking. Information Sciences, Volume 496, Pages 378-398.

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(2019). Multi-target feature selection through output space clustering. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN).

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(2018). Toward an Understanding of Adversarial Examples in Clinical Trials. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML/PKDD). Acceptance rate 92/354 (26%).

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(2018). Distinguishing Prognostic and Predictive Biomarkers: An Information Theoretic Approach. Bioinformatics, volume 34(19), pages 3365–3376.

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(2018). On the Stability of Feature Selection Algorithms. Journal of Machine Learning Research (JMLR), volume 18(174), pages 1-54.

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(2018). Simple strategies for semi-supervised feature selection. Machine Learning Journal (MLJ), volume 107(2), pages 357-395.

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(2017). On the Use of Spearman's Rho to Measure the Stability of Feature Rankings. Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA).

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(2017). Dealing with under-reported variables: An information theoretic solution. International Journal of Approximate Reasoning, volume 85, pages 159-177.

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(2017). Exploring the consequences of distributed feature selection in DNA microarray data. International Joint Conference on Neural Networks (IJCNN).

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(2017). Disentangling Prognostic and Predictive Biomarkers Through Mutual Information. Informatics for Health (I4H).

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(2017). Algorithmic challenges in Big Data analytics. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN).

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(2016). Ranking Biomarkers Through Mutual Information. NIPS Workshop on Machine Learning for Health (ML4HC).

arXiv

(2016). Estimating mutual information in under-reported variables. International Conference on Probabilistic Graphical Models (PGM).

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(2015). Markov blanket discovery in positive-unlabelled and semi-supervised data. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML/PKDD). Acceptance rate 89/383 (23.2%).

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(2015). Hypothesis Testing and Feature Selection in Semi-supervised Data. PhD Thesis, School of Computer Science, University of Manchester, UK.
PhD supervisor: Professor Gavin Brown.
AWARD Best PhD Thesis Prize of the School of Computer Science at the University of Manchester 2016 (sponsored by IBM).

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(2014). Statistical Hypothesis Testing in Positive Unlabelled Data. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML/PKDD). Acceptance rate 115/483 (23.8%).
AWARD Best Student Paper Award in ECML/PKDD 2014 (sponsored by Springer).
AWARD Runner up Best Paper Prize of the School of Computer Science at the University of Manchester 2014 (sponsored by IBM).

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(2014). Information theoretic feature selection in multi-label data through composite likelihood. Structural, Syntactic, and Statistical Pattern Recognition (SSPR).

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(2011). On the Stratification of Multi-label Data. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML/PKDD). Acceptance rate 121/599 (20%).

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(2011). MLKDs Participation at the CLEF 2011 Photo Annotation and Concept-Based Retrieval Tasks. ImageClef Lab of CLEF Conference on Multilingual and Multimodal Information Access Evaluation.

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(2011). Multi-label machine learning algorithms for automated image annotation. MSc Thesis, School of Informatics, Aristotle University of Thessaloniki, Greece.
Thesis supervisor: Assistant Professor Grigorios Tsoumakas..

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