Theodoros Evgeniou

According to our database, Theodoros Evgeniou authored at least 46 papers between 1997 and 2023.

Collaborative distances:

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

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

Manipulation Risks in Explainable AI: The Implications of the Disagreement Problem.

Sofie Goethals, David Martens, Theodoros Evgeniou

CoRR, 2023

2022

The non-linear nature of the cost of comprehensibility.

Sofie Goethals, David Martens, Theodoros Evgeniou

J. Big Data, 2022

2021

Direct-to-consumer medical machine learning and artificial intelligence applications.

Boris Babic, Sara Gerke, Theodoros Evgeniou, I. Glenn Cohen

Nat. Mach. Intell., 2021

Understanding Consumer Preferences for Explanations Generated by XAI Algorithms.

Yanou Ramon, Tom Vermeire, Olivier Toubia, David Martens, Theodoros Evgeniou

CoRR, 2021

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

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

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

Metafeatures-based Rule-Extraction for Classifiers on Behavioral and Textual Data.

Yanou Ramon, David Martens, Theodoros Evgeniou, Stiene Praet

CoRR, 2020

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

2019

Counterfactual Explanation Algorithms for Behavioral and Textual Data.

Yanou Ramon, David Martens, Foster J. Provost, Theodoros Evgeniou

CoRR, 2019

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

Proceedings of the Medical Imaging 2019: Image Processing, 2019

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, Anne Bertrand, Hugo Bertin, Marie Odile Habert, Stanley Durrleman, Theodoros Evgeniou, Olivier Colliot

NeuroImage, 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, Anne Bertrand, Hugo Bertin, Marie Odile Habert, Stanley Durrleman, Theodoros Evgeniou, Olivier Colliot, Alzheimer's Disease Neuroimaging Initiative

CoRR, 2018

2017

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

Proceedings of the Machine Learning in Medical Imaging - 8th International Workshop, 2017

2015

Iteratively refining SVMs using priors.

Enric Junqué de Fortuny, Theodoros Evgeniou, David Martens, Foster J. Provost

Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

2013

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

2012

Content Contributor Management and Network Effects in a UGC Environment.

Kaifu Zhang, Theodoros Evgeniou, Vineet Padmanabhan, Emile Richard

Mark. Sci., 2012

A Regularization Approach for Prediction of Edges and Node Features in Dynamic Graphs

Emile Richard, Andreas Argyriou, Theodoros Evgeniou, Nicolas Vayatis

CoRR, 2012

2010

Link Discovery using Graph Feature Tracking.

Emile Richard, Nicolas Baskiotis, Theodoros Evgeniou, Nicolas Vayatis

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

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

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

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

Convex multi-task feature learning.

Andreas Argyriou, Theodoros Evgeniou, Massimiliano Pontil

Mach. Learn., 2008

Emerging Machine Learning Techniques in Signal Processing.

Theodoros Evgeniou, Aníbal R. Figueiras-Vidal, Sergios Theodoridis

EURASIP J. Adv. Signal Process., 2008

2006

Low-rank matrix factorization with attributes

Jacob D. Abernethy, Francis R. Bach, Theodoros Evgeniou, Jean-Philippe Vert

CoRR, 2006

Multi-Task Feature Learning.

Andreas Argyriou, Theodoros Evgeniou, Massimiliano Pontil

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

2005

Learning Multiple Tasks with Kernel Methods.

Theodoros Evgeniou, Charles A. Micchelli, Massimiliano Pontil

J. Mach. Learn. Res., 2005

Stability of Randomized Learning Algorithms.

André Elisseeff, Theodoros Evgeniou, Massimiliano Pontil

J. Mach. Learn. Res., 2005

2004

Leave One Out Error, Stability, and Generalization of Voting Combinations of Classifiers.

Theodoros Evgeniou, Massimiliano Pontil, André Elisseeff

Mach. Learn., 2004

Regularized multi--task learning.

Theodoros Evgeniou, Massimiliano Pontil

Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

2003

Image Representations and Feature Selection for Multimedia Database Search.

Theodoros Evgeniou, Massimiliano Pontil, Constantine Papageorgiou, Tomaso A. Poggio

IEEE Trans. Knowl. Data Eng., 2003

2002

Learning Preference Relations from Data.

Theodoros Evgeniou, Massimiliano Pontil

Proceedings of the Neural Nets, 13th Italian Workshop on Neural Nets, 2002

Support Vector Machines with Clustering for Training with Very Large Datasets.

Theodoros Evgeniou, Massimiliano Pontil

Proceedings of the Methods and Applications of Artificial Intelligence, 2002

A Simple Algorithm for Learning Stable Machines.

Savina Andonova, André Elisseeff, Theodoros Evgeniou, Massimiliano Pontil

Proceedings of the 15th European Conference on Artificial Intelligence, 2002

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

Support Vector Machines: Theory and Applications.

Theodoros Evgeniou, Massimiliano Pontil

Proceedings of the Machine Learning and Its Applications, Advanced Lectures, 2001

2000

Learning with kernel machine architectures.

Theodoros Evgeniou

PhD thesis, 2000

Dynamic pricing in a reputation-brokered agent-mediated marketplace.

Giorgos Zacharia, Theodoros Evgeniou, Pattie Maes

Intell. Syst. Account. Finance Manag., 2000

Statistical Learning Theory: A Primer.

Theodoros Evgeniou, Massimiliano Pontil, Tomaso A. Poggio

Int. J. Comput. Vis., 2000

Regularization Networks and Support Vector Machines.

Theodoros Evgeniou, Massimiliano Pontil, Tomaso A. Poggio

Adv. Comput. Math., 2000

Bounds on the Generalization Performance of Kernel Machine Ensembles.

Theodoros Evgeniou, Luis Pérez-Breva, Massimiliano Pontil, Tomaso A. Poggio

Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

A Note on the Generalization Performance of Kernel Classifiers with Margin.

Theodoros Evgeniou, Massimiliano Pontil

Proceedings of the Algorithmic Learning Theory, 11th International Conference, 2000

1999

From regression to classification in support vector machines.

Massimiliano Pontil, Ryan M. Rifkin, Theodoros Evgeniou

Proceedings of the 7th European Symposium on Artificial Neural Networks, 1999

On the V_gamma Dimension for Regression in Reproducing Kernel Hilbert Spaces.

Theodoros Evgeniou, Massimiliano Pontil

Proceedings of the Algorithmic Learning Theory, 10th International Conference, 1999

1997

Image-based view synthesis by combining trilinear tensors and learning techniques.

Shai Avidan, Theodoros Evgeniou, Amnon Shashua, Tomaso A. Poggio

Proceedings of the ACM Symposium on Virtual Reality Software and Technology, 1997