Roberto D'Ambrosio

Learning to Rank with Deep Neural Networks

Salim Jouili, C. Louvain, A. Cherif, 2016 .

Kernel methods for heterogeneous feature selection

Pierre Dupont, Roberto D'Ambrosio, Jérôme Paul, 2015, Neurocomputing.

Handling imbalanced datasets by reconstruction rules in decomposition schemes. (Classification de bases de données déséquilibrées par des règles de décomposition)

Roberto D'Ambrosio, Roberto D'Ambrosio, 2014 .

Polichotomies on Imbalanced Domains by One-per-Class Compensated Reconstruction Rule

Paolo Soda, Roberto D'Ambrosio, Roberto D'Ambrosio, 2012, SSPR/SPR.

Biomedical Images Classification by Universal Nearest Neighbours Classifier Using Posterior Probability

Frank Nielsen, Richard Nock, Michel Barlaud, 2012, MLMI.

Boosting Nearest Neighbors for the Efficient Estimation of Posteriors

Frank Nielsen, Richard Nock, Michel Barlaud, 2012, ECML/PKDD.

Boosting Stochastic Newton Descent for Bigdata large scale classification

Michel Barlaud, Roberto D'Ambrosio, Wafa Belhajali, 2014, 2014 IEEE International Conference on Big Data (Big Data).

Gentle Nearest Neighbors Boosting over Proper Scoring Rules

Frank Nielsen, Richard Nock, Michel Barlaud, 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A mixture Cox-Logistic model for feature selection from survival and classification data pdf

Pierre Dupont, Samuel Branders, Roberto D'Ambrosio, 2015, ArXiv.

The Coxlogit model: Feature selection from survival and classification data

Pierre Dupont, Samuel Branders, Roberto D'Ambrosio, 2014, 2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM).