88 documents
- Fabien Labernia, Florian Yger, Brice Mayag, Jamal Atif. Query-based learning of acyclic conditional preference networks from contradictory preferences. EURO journal on decision processes, 2018, 6 (1-2), pp.39-59. ⟨10.1007/s40070-017-0070-3⟩. ⟨hal-02074081⟩
- Fabien Labernia, Bruno Zanuttini, Brice Mayag, Florian Yger, Jamal Atif. Online learning of acyclic conditional preference networks from noisy data. 17th IEEE International Conference on Data Mining (ICDM 2017), Nov 2017, New Orleans, United States. ⟨hal-01619969⟩
- Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski, Francois Fagan, Cedric Gouy-Pailler, et al.. Structured adaptive and random spinners for fast machine learning computations. 20th International Conference on Artificial Intelligence and Statistics (AISTATS 2017), Apr 2017, Fort Lauderdale, Florida, United States. pp.1020-1029. ⟨hal-02010086⟩
- Fabien Labernia, Bruno Zanuttini, Brice Mayag, Florian Yger, Jamal Atif. Online learning of acyclic conditional preference networks from noisy data. ICDM 2017, 2017, New Orleans, United States. ⟨10.1109/ICDM.2017.34⟩. ⟨hal-02074110⟩
- Adrian Lecoutre, Benjamin Negrevergne, Florian Yger. Recognizing Art Style Automatically with deep learning. Proceedings of Machine Learning Research, 2017, 77, pp.327 - 342. ⟨hal-02004781⟩
- Quentin Brabant, Miguel Couceiro, Fabien Labernia, Amedeo Napoli. A dimensionality Reduction Approach for Qualitative Preference Aggregation. International Symposium on Aggregation and Structures (ISAS 2016), Jul 2016, Luxembourg, Luxembourg. ⟨hal-02074061⟩
- Eric Benhamou. T-statistic for Autoregressive process. Journal of Statistical and Econometric Methods, 2011, 1, pp.2241 - 0376. ⟨hal-02012459⟩
- Eric Benhamou. Gram Charlier and Edgeworth expansion for sample variance. Theoretical Mathematics and Applications, 2011, x (4), pp.1792 - 6939. ⟨hal-02012464⟩
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