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Léa Laporte
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Journal Articles
- 2020
- [j5]Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Liyun He-Guelton, Olivier Caelen, Michael Granitzer, Sylvie Calabretto:
Towards automated feature engineering for credit card fraud detection using multi-perspective HMMs. Future Gener. Comput. Syst. 102: 393-402 (2020) - 2018
- [j4]Gilles Hubert
, Yoann Pitarch, Karen Pinel-Sauvagnat
, Ronan Tournier, Léa Laporte:
TournaRank: When retrieval becomes document competition. Inf. Process. Manag. 54(2): 252-272 (2018) - 2015
- [j3]Léa Laporte, Sébastien Déjean
, Josiane Mothe:
Sélection de variables en apprentissage d'ordonnancement. Évaluation des SVM pondérés. Document Numérique 18(1): 97-121 (2015) - 2014
- [j2]Léa Laporte, Rémi Flamary
, Stéphane Canu
, Sébastien Déjean
, Josiane Mothe:
Nonconvex Regularizations for Feature Selection in Ranking With Sparse SVM. IEEE Trans. Neural Networks Learn. Syst. 25(6): 1118-1130 (2014) - 2013
- [j1]Léa Laporte:
De l'apprentissage d'ordonnancement à l'adaptation au contexte. État de l'art et propositions. Document Numérique 16(1): 97-121 (2013)
Conference and Workshop Papers
- 2021
- [c22]Lu Gan, Diana Nurbakova, Léa Laporte, Sylvie Calabretto:
Recommandation diversifiée via des processus ponctuels déterminantaux sur des graphes de connaissances. EGC 2021: 365-372 - [c21]Lu Gan, Diana Nurbakova, Léa Laporte, Sylvie Calabretto:
EMDKG: Improving Accuracy-Diversity Trade-Off in Recommendation with EM-based Model and Knowledge Graph Embedding. WI/IAT 2021: 17-24 - 2020
- [c20]Lu Gan, Diana Nurbakova
, Léa Laporte, Sylvie Calabretto:
Enhancing Recommendation Diversity using Determinantal Point Processes on Knowledge Graphs. SIGIR 2020: 2001-2004 - 2019
- [c19]Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Sylvie Calabretto, Liyun He-Guelton, Frédéric Oblé, Michael Granitzer:
Dataset Shift Quantification for Credit Card Fraud Detection. AIKE 2019: 97-100 - [c18]Diana Nurbakova
, Léa Laporte, Sylvie Calabretto, Jérôme Gensel:
DEvIR: Data Collection and Analysis for the Recommendation of Events and Itineraries. HICSS 2019: 1-10 - [c17]Josiane Mothe, Léa Laporte, Adrian-Gabriel Chifu:
Predicting Query Difficulty in IR: Impact of Difficulty Definition. KSE 2019: 1-6 - [c16]Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Sylvie Calabretto, Olivier Caelen, Liyun He-Guelton, Michael Granitzer
:
Multiple perspectives HMM-based feature engineering for credit card fraud detection. SAC 2019: 1359-1361 - 2018
- [c15]Giovanni Ciccone, Arthur Sultan, Léa Laporte, Elöd Egyed-Zsigmond, Alaa Alhamzeh, Michael Granitzer:
Stacked Gender Prediction from Tweet Texts and Images: Notebook for PAN at CLEF 2018. CLEF (Working Notes) 2018 - [c14]Gilles Hubert, Yoann Pitarch, Karen Pinel-Sauvagnat, Ronan Tournier, Léa Laporte:
TournaRank : Quand la Recherche d'Information devient un tournoi entre documents. CORIA 2018 - [c13]Diana Nurbakova
, Léa Laporte, Sylvie Calabretto, Jérôme Gensel:
Recommandation de séquences d'activités lors d'événements distribués. CORIA 2018 - [c12]Adrian-Gabriel Chifu
, Léa Laporte, Josiane Mothe, Md. Zia Ullah:
Query Performance Prediction Focused on Summarized Letor Features. SIGIR 2018: 1177-1180 - 2017
- [c11]Guillaume Kheng, Léa Laporte, Michael Granitzer:
INSA LYON and UNI PASSAU's Participation at PAN@CLEF'17: Author Profiling task. CLEF (Working Notes) 2017 - [c10]Diana Nurbakova
, Léa Laporte, Sylvie Calabretto, Jérôme Gensel
:
Recommendation of Short-Term Activity Sequences During Distributed Events. ICCS 2017: 2069-2078 - [c9]Diana Nurbakova
, Léa Laporte, Sylvie Calabretto, Jérôme Gensel
:
Users psychological profiles for leisure activity recommendation: user study. CitRec@RecSys 2017: 3:1-3:4 - [c8]Diana Nurbakova
, Léa Laporte, Sylvie Calabretto, Jérôme Gensel:
Itinerary Recommendation for Cruises: User Study. RecTour@RecSys 2017: 31-34 - 2016
- [c7]Diana Nurbakova
, Léa Laporte, Sylvie Calabretto, Jérôme Gensel:
ANASTASIA : recommandation de séquences d'activités spatiotemporelles. CORIA-CIFED 2016: 325-334 - [c6]Antoine Boutet, Albin Petit, Sonia Ben Mokhtar
, Léa Laporte:
Leveraging Query Sensitivity for Practical Private Web Search. Middleware Posters and Demos 2016: 5-6 - 2015
- [c5]Adrian-Gabriel Chifu, Léa Laporte, Josiane Mothe:
La prédiction efficace de la difficulté des requêtes : une tâche impossible? CORIA 2015: 189-204 - 2014
- [c4]Léa Laporte, Sébastien Déjean, Josiane Mothe:
Séparateurs à Vaste Marge pondérés en norme L2 pour la sélection de variables en apprentissage d'ordonnancement. CORIA-CIFED 2014: 321-336 - 2013
- [c3]Estelle Delpech, Laurent Candillier, Léa Laporte, Samuel Phan:
Identification de compatibilités entre descripteurs de lieux et apprentissage automatique. EGC 2013: 311-316 - [c2]Léa Laporte, Sébastien Déjean, Josiane Mothe:
Multiple Clicks Model for Web Search of Multi-clickable Documents. ICEIS (1) 2013: 298-303 - 2012
- [c1]Léa Laporte, Laurent Candillier, Sébastien Déjean, Josiane Mothe:
Évaluation de la pertinence dans les moteurs de recherche géoréférencés . INFORSID 2012: 281-298
Informal and Other Publications
- 2019
- [i4]Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Olivier Caelen, Liyun He-Guelton, Sylvie Calabretto, Michael Granitzer:
Multiple perspectives HMM-based feature engineering for credit card fraud detection. CoRR abs/1905.06247 (2019) - [i3]Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Sylvie Calabretto, Liyun He-Guelton, Frédéric Oblé, Michael Granitzer:
Dataset shift quantification for credit card fraud detection. CoRR abs/1906.06977 (2019) - [i2]Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Liyun He-Guelton, Olivier Caelen, Michael Granitzer, Sylvie Calabretto:
Towards automated feature engineering for credit card fraud detection using multi-perspective HMMs. CoRR abs/1909.01185 (2019) - 2015
- [i1]Léa Laporte, Rémi Flamary, Stéphane Canu, Sébastien Déjean
, Josiane Mothe:
Non-convex Regularizations for Feature Selection in Ranking With Sparse SVM. CoRR abs/1507.00500 (2015)
Coauthor Index
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