Marchand M, Hongyu S, Morvant E, Rousu J, Shawe Taylor J. 2014. Multilabel structured output learning with random spanning trees of max-margin Markov networks. NIPS: Neural Information Processing Systems.
LibreCat: https://research-explorer.ista.ac.at/record/2051

Morvant E, Habrard A, Ayache S. 2014. Majority vote of diverse classifiers for late fusion. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). IAPR: International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, LNCS, vol. 8621, 153–162.
LibreCat: https://research-explorer.ista.ac.at/record/2057
DOI: 10.1007/978-3-662-44415-3_16
arXiv: 1404.7796

Morvant E. 2014. Domain Adaptation of Weighted Majority Votes via Perturbed Variation-Based Self-Labeling. Pattern Recognition Letters. 51, 37–43.
LibreCat: https://research-explorer.ista.ac.at/record/2165
DOI: 10.1016/j.patrec.2014.08.013

Bellet A, Habrard A, Morvant E, Sebban M. 2014. Learning a priori constrained weighted majority votes. Machine Learning. 97(1–2), 129–154.
LibreCat: https://research-explorer.ista.ac.at/record/2180
DOI: 10.1007/s10994-014-5462-z

Morvant E. 2014. Adaptation de domaine de vote de majorité par auto-étiquetage non itératif. CAP: Conférence Francophone sur l’Apprentissage Automatique (Machine Learning French Conference) vol. 1, 49–58.
LibreCat: https://research-explorer.ista.ac.at/record/2189