Image-based view synthesis by combining trilinear tensors and learning techniques. - Shai Avidan; Theodoros Evgeniou; Amnon Shashua; Tomaso A. Poggio (VRST, 1997)

On the Vgamma Dimension for Regression in Reproducing Kernel Hilbert Spaces. - Theodoros Evgeniou; Massimiliano Pontil (ALT, 1999)

From regression to classification in support vector machines. - Massimiliano Pontil; Ryan M. Rifkin; Theodoros Evgeniou (ESANN, 1999)

A Note on the Generalization Performance of Kernel Classifiers with Margin. - Theodoros Evgeniou; Massimiliano Pontil (ALT, 2000)

Bounds on the Generalization Performance of Kernel Machine Ensembles. - Theodoros Evgeniou; Luis Pérez-Breva; Massimiliano Pontil; Tomaso A. Poggio (ICML, 2000)

Regularization Networks and Support Vector Machines. - Theodoros Evgeniou; Massimiliano Pontil; Tomaso A. Poggio (Adv. Comput. Math., 2000)

Statistical Learning Theory: A Primer. - Theodoros Evgeniou; Massimiliano Pontil; Tomaso A. Poggio (Int. J. Comput. Vis., 2000)

Dynamic pricing in a reputation-brokered agent-mediated marketplace. - Giorgos Zacharia; Theodoros Evgeniou; Pattie Maes (Intell. Syst. Account. Finance Manag., 2000)

Learning with kernel machine architectures. - Theodoros Evgeniou (2000)

Support Vector Machines: Theory and Applications. - Theodoros Evgeniou; Massimiliano Pontil (Machine Learning and Its Applications, 2001)

Economics of Dynamic Pricing in a Reputation Brokered Agent Mediated Marketplace. - Giorgos Zacharia; Theodoros Evgeniou; Alexandros Moukas; Petros Boufounos; Pattie Maes (Electron. Commer. Res., 2001)

A Simple Algorithm for Learning Stable Machines. - Savina Andonova; André Elisseeff; Theodoros Evgeniou; Massimiliano Pontil (ECAI, 2002)

Support Vector Machines with Clustering for Training with Very Large Datasets. - Theodoros Evgeniou; Massimiliano Pontil (SETN, 2002)

Learning Preference Relations from Data. - Theodoros Evgeniou; Massimiliano Pontil (WIRN, 2002)

Image Representations and Feature Selection for Multimedia Database Search. - Theodoros Evgeniou; Massimiliano Pontil; Constantine Papageorgiou; Tomaso A. Poggio (IEEE Trans. Knowl. Data Eng., 2003)

Regularized multi–task learning. - Theodoros Evgeniou; Massimiliano Pontil (KDD, 2004)

Leave One Out Error, Stability, and Generalization of Voting Combinations of Classifiers. - Theodoros Evgeniou; Massimiliano Pontil; André Elisseeff (Mach. Learn., 2004)

Stability of Randomized Learning Algorithms. - André Elisseeff; Theodoros Evgeniou; Massimiliano Pontil (J. Mach. Learn. Res., 2005)

Learning Multiple Tasks with Kernel Methods. - Theodoros Evgeniou; Charles A. Micchelli; Massimiliano Pontil (J. Mach. Learn. Res., 2005)

Multi-Task Feature Learning. - Andreas Argyriou; Theodoros Evgeniou; Massimiliano Pontil (NIPS, 2006)

Low-rank matrix factorization with attributes - Jacob D. Abernethy; Francis R. Bach; Theodoros Evgeniou; Jean-Philippe Vert (CoRR, 2006)

Emerging Machine Learning Techniques in Signal Processing. - Theodoros Evgeniou; Aníbal R. Figueiras-Vidal; Sergios Theodoridis (EURASIP J. Adv. Signal Process., 2008)

Convex multi-task feature learning. - Andreas Argyriou; Theodoros Evgeniou; Massimiliano Pontil (Mach. Learn., 2008)

Eliciting Consumer Preferences Using Robust Adaptive Choice Questionnaires. - Jacob D. Abernethy; Theodoros Evgeniou; Olivier Toubia; Jean-Philippe Vert (IEEE Trans. Knowl. Data Eng., 2008)

Implementation of collaborative e-supply-chain initiatives: an initial challenging and final success case from grocery retailing. - Katerina Pramatari; Theodoros Evgeniou; Georgios I. Doukidis (J. Inf. Technol., 2009)

A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization. - Jacob D. Abernethy; Francis R. Bach; Theodoros Evgeniou; Jean-Philippe Vert (J. Mach. Learn. Res., 2009)

Link Discovery using Graph Feature Tracking. - Emile Richard; Nicolas Baskiotis; Theodoros Evgeniou; Nicolas Vayatis (NIPS, 2010)

A Regularization Approach for Prediction of Edges and Node Features in Dynamic Graphs - Emile Richard; Andreas Argyriou; Theodoros Evgeniou; Nicolas Vayatis (CoRR, 2012)

Content Contributor Management and Network Effects in a UGC Environment. - Kaifu Zhang; Theodoros Evgeniou; Vineet Padmanabhan; Emile Richard (Mark. Sci., 2012)

Dynamic Experiments for Estimating Preferences: An Adaptive Method of Eliciting Time and Risk Parameters. - Olivier Toubia; Eric Johnson; Theodoros Evgeniou; Philippe Delquié (Manag. Sci., 2013)

Iteratively refining SVMs using priors. - Enric Junqué de Fortuny; Theodoros Evgeniou; David Martens; Foster J. Provost (IEEE BigData, 2015)

Yet Another ADNI Machine Learning Paper? Paving the Way Towards Fully-Reproducible Research on Classification of Alzheimer's Disease. - Jorge Samper-González; Ninon Burgos; Sabrina Fontanella; Hugo Bertin; Marie Odile Habert; Stanley Durrleman; Theodoros Evgeniou; Olivier Colliot (MLMI@MICCAI, 2017)

Reproducible evaluation of classification methods in Alzheimer's disease: framework and application to MRI and PET data. - Jorge Samper-González; Ninon Burgos; Simona Bottani; Sabrina Fontanella; Pascal Lu; Arnaud Marcoux; Alexandre Routier; Jérémy Guillon; Michael Bacci; Junhao Wen 002; Anne Bertrand; Hugo Bertin; et al. (CoRR, 2018)

Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data. - Jorge Samper-González; Ninon Burgos; Simona Bottani; Sabrina Fontanella; Pascal Lu; Arnaud Marcoux; Alexandre Routier; Jérémy Guillon; Michael Bacci; Junhao Wen 002; Anne Bertrand; Hugo Bertin; et al. (NeuroImage, 2018)

Reproducible evaluation of methods for predicting progression to Alzheimer's disease from clinical and neuroimaging data. - Jorge Samper-González; Ninon Burgos; Simona Bottani; Marie Odile Habert; Theodoros Evgeniou; Stéphane Epelbaum; Olivier Colliot (Image Processing, 2019)

Counterfactual Explanation Algorithms for Behavioral and Textual Data. - Yanou Ramon; David Martens; Foster J. Provost; Theodoros Evgeniou (CoRR, 2019)

A comparison of instance-level counterfactual explanation algorithms for behavioral and textual data: SEDC, LIME-C and SHAP-C. - Yanou Ramon; David Martens; Foster J. Provost; Theodoros Evgeniou (Adv. Data Anal. Classif., 2020)

Metafeatures-based Rule-Extraction for Classifiers on Behavioral and Textual Data. - Yanou Ramon; David Martens; Theodoros Evgeniou; Stiene Praet (CoRR, 2020)

A benchmarking study of classification techniques for behavioral data. - Sofie De Cnudde; David Martens; Theodoros Evgeniou; Foster J. Provost (Int. J. Data Sci. Anal., 2020)

SEAIR Framework Accounting for a Personalized Risk Prediction Score: Application to the Covid-19 Epidemic. - Olivier Boulant; Mathilde Fekom; Camille Pouchol; Theodoros Evgeniou; Anton Ovchinnikov; Raphaël Porcher; Nicolas Vayatis (Image Process. Line, 2020)

The need for a system view to regulate artificial intelligence/machine learning-based software as medical device. - Sara Gerke; Boris Babic; Theodoros Evgeniou; I. Glenn Cohen (npj Digit. Medicine, 2020)

Understanding Consumer Preferences for Explanations Generated by XAI Algorithms. - Yanou Ramon; Tom Vermeire; Olivier Toubia; David Martens; Theodoros Evgeniou (CoRR, 2021)

Direct-to-consumer medical machine learning and artificial intelligence applications. - Boris Babic; Sara Gerke; Theodoros Evgeniou; I. Glenn Cohen (Nat. Mach. Intell., 2021)

The non-linear nature of the cost of comprehensibility. - Sofie Goethals; David Martens; Theodoros Evgeniou (J. Big Data, 2022)

Manipulation Risks in Explainable AI: The Implications of the Disagreement Problem. - Sofie Goethals; David Martens; Theodoros Evgeniou (PKDD/ECML Workshops (3), 2023)

How AI can learn from the law: putting humans in the loop only on appeal. - I. Glenn Cohen; Boris Babic; Sara Gerke; Qiong Xia; Theodoros Evgeniou; Klaus Wertenbroch (npj Digit. Medicine, 2023)

Algorithmovigilance, lessons from pharmacovigilance. - Alan Balendran; Mehdi Benchoufi; Theodoros Evgeniou; Philippe Ravaud (npj Digit. Medicine, 2024)

Can metafeatures help improve explanations of prediction models when using behavioral and textual data? - Yanou Ramon; David Martens; Theodoros Evgeniou; Stiene Praet (Mach. Learn., 2024)

Tell me a story! Narrative-driven XAI with Large Language Models. - David Martens; James Hinns; Camille Dams; Mark Vergouwen; Theodoros Evgeniou (Decis. Support Syst., 2025)

A scoping review of robustness concepts for machine learning in healthcare. - Alan Balendran; Céline Beji; Florie Bouvier; Ottavio Khalifa; Theodoros Evgeniou; Philippe Ravaud; Raphaël Porcher (npj Digit. Medicine, 2025)

Evaluation and Facilitation of Online Discussions in the LLM Era: A Survey. - Katerina Korre; Dimitris Tsirmpas; Nikos Gkoumas; Emma Cabalé; Dionysis Kontarinis; Danai Myrtzani; Theodoros Evgeniou; Ion Androutsopoulos; John Pavlopoulos (CoRR, 2025)

Beware of "Explanations" of AI. - David Martens; Galit Shmueli; Theodoros Evgeniou; Kevin Bauer; Christian Janiesch; Stefan Feuerriegel; Sebastian Gabel; Sofie Goethals; Travis Greene; Nadja Klein; Mathias Kraus; Niklas Kühl 001; et al. (CoRR, 2025)