3 Аспиранты (Научны(е)й руководител(и)ь / Со-руководитель)

• CRILOUT Mathieu : DeLeTe : Deep Learning for Temporal Graph
• GÉRALD Thomas : neural network and representation learning for modeling rich dynamic Data
• YIN Yuan : Méthodes neuronales génératives pour la modélisation de séquences

1 Кандидат наук 2016

Публикации 2010-2019

• 2019
  • V. Guiguet, P. Cribier‑Delande, N. Baskiotis, V. Guigue : “Prédiction de séries temporelles multi-variées stationnaires: modélisation du contexte pour l’analyse des données de transports”, GRETSI 2019, Lille, France (2019)
  • N. Baskiotis, L. Becirspahic, R. Brault, S. Duguet, V. Guigue, V. Guiguet, S. Lorin, V. Thouvenot : “A Deep Approach of Affluence Forecasting in Subway Networks”, WCRR 2019 - 12^th World Congress on Railway Research, Tokyo, Japan (2019)
• 2018
  • E. Tonnelier, N. Baskiotis, V. Guigue, P. Gallinari : “Anomaly detection in smart card logs and distant evaluation with Twitter: a robust framework”, Neurocomputing, vol. 298, pp. 109-121, (Elsevier) (2018)
  • E. Tonnelier, N. Baskiotis, V. Guigue, P. Gallinari : “Factorisation de Tenseurs pour l’analyse de réseaux de mobilité”, 1^ères Rencontres Francophones Transport-Mobilité (RFTM), Lyon, France (2018)
• 2017
  • E. Tonnelier, N. Baskiotis, V. Guigue, P. Gallinari : “Anomaly detection and characterization in smart card logs using NMF and Tweets”, ESANN 2017 - 25^th European Symposium on Artificial Neural Networks, Bruges, Belgium (2017)
• 2016
  • C. Delauney, N. Baskiotis, V. Guigue : “Trajectory Bayesian Indexing : The Airport Ground Traffic Case”, ITSC 2016 - 19^th IEEE Intelligent Transportation Systems Conference, Rio de Janeiro, Brazil (2016)
  • Z. Kraljevic, N. Baskiotis, B. Piwowarski, P. Gallinari : “Représentation temporelle des mots : application au clustering de micro-blogs.”, Conférence en Recherche d'Infomations et Applications, Toulouse, France, pp. 531-544 (2016)
  • A. Ziat, B. Leroy, N. Baskiotis, L. Denoyer : “Joint prediction of road-traffic and parking occupancy over a city with representation learning”, 19^th IEEE International Conference on Intelligent Transportation Systems, Rio de Janeiro, Brazil (2016)
  • A. Ziat, G. Contardo, N. Baskiotis, L. Denoyer : “Learning Embeddings for Completion and Prediction of Relationnal Multivariate Time-Series”, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - ESANN, Unknown, (2016)
  • E. Tonnelier, N. Baskiotis, V. Guigue, P. Gallinari : “Smart card in public transportation: designing a analysis system at the human scale”, ITSC, Rio de Janeiro, Brazil (2016)
  • Ch. Dhanjal, N. Baskiotis, S. Clémençon, N. Usunier : “An empirical comparison of V -fold penalisation and cross-validation for model selection in distribution-free regression”, Pattern Analysis and Applications, vol. 19 (1), pp. 41-53, (Springer Verlag) (2016)
  • S. Clémençon, N. Baskiotis, N. Vayatis : “Anomaly Ranking in a High Dimensional Space: The Unsupervised TreeRank Algorithm”, chapter in Unsupervised Learning Algorithms, pp. 33-54, (Springer International Publishing), (ISBN: 978-3-319-24211-8) (2016)
  • M. Poussevin, E. Tonnelier, N. Baskiotis, V. Guigue, P. Gallinari : “Mining ticketing logs for usage characterization with nonnegative matrix factorization”, chapter in Big Data Analytics in the Social and Ubiquitous Context, vol. 9546, Lecture Notes in Computer Science, pp. 147-164, (Springer), (ISBN: 978-3-319-29008-9) (2016)
• 2015
  • G. Tsatsaronis, G. Balikas, P. Malakasiotis, I. Partalas, M. Zschunke, M. Alvers, D. Weissenborn, A. Krithara, S. Petridis, D. Polychronopoulos, Y. Almirantis, J. Pavlopoulos, N. Baskiotis, P. Gallinari, Th. Artières, A.‑C. Ngonga Ngomo, N. Heino, E. Gaussier, L. Barrio‑Alvers, M. Schroeder, I. Androutsopoulos, G. Paliouras : “An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition”, BMC Bioinformatics, vol. 16 (1), pp. 138, (BioMed Central) (2015)
  • S. Lamprier, N. Baskiotis, T. Ziadi, L. Hillah : “The CARE Platform for the Analysis of Behavior Model Inference Techniques”, Information and Software Technology, vol. 60, pp. 32-50, (Elsevier) (2015)
  • I. Partalas, A. Kosmopoulos, N. Baskiotis, Th. Artières, G. Paliouras, E. Gaussier, I. Androutsopoulos, M.‑R. Amini, P. Gallinari : “LSHTC: A Benchmark for Large-Scale Text Classification”, (2015)
  • R. Puget, N. Baskiotis : “Hierarchical Label Partitioning for Large Scale Classification”, IEEE International Conference on Data Science and Advanced Analytics, DSAA'2015, Paris, France (2015)
  • R. Puget, N. Baskiotis, P. Gallinari : “Sequential Dynamic Classification for Large Scale Multiclass Problems”, Extreme Classification Workshop at ICML, Lille, France (2015)
  • A. Ziat, G. Contardo, N. Baskiotis, L. Denoyer : “Car-traffic forecasting: A representation learning approach”, Workshop MUD, Mining Urban Data 201, Unknown, (2015)
  • G. Balikas, N. Baskiotis : “Detecting Influence in User-Activity Logs”, International Conference on Computational Social Science (ICCSS), Helsinki, Finland (2015)
• 2014
  • M. Poussevin, N. Baskiotis, V. Guigue, P. Gallinari : “Mining ticketing logs for usage characterization with nonnegative matrix factorization”, SenseML 2014 -- ECML Workshop, Nancy, France (2014)
  • S. Lamprier, T. Ziadi, N. Baskiotis, L. Hillah : “Exact and Efficient Temporal Steering of Software Behavioral Model Inference”, Proc. of 19^th IEEE International Conference on Engineering of Complex Computer Systems (ICECCS), Tianjin, China, pp. 166-175, (IEEE) (2014)
  • M. Poussevin, N. Baskiotis, V. Guigue, P. Gallinari : “Factorisation matricielle sous contraintes pour l’analyse des usages du métro parisien”, CAp'2014 : Conférence d'Apprentissage Automatique, Saint-Etienne, France (2014)
  • R. Puget, N. Baskiotis, P. Gallinari : “Scalable Learnability Measure for Hierarchical Learning in Large Scale Multi-Class Classification”, WSDM Workshop Web-Scale Classification: Classifying Big Data from the Web, New York, United States (2014)
• 2013
  • S. Lamprier, N. Baskiotis, T. Ziadi, L. Hillah : “CARE: a platform for reliable Comparison and Analysis of Reverse-Engineering techniques”, 18^th IEEE International Conference on Engineering of Complex Computer Systems -- ICECCS, Singapore, Singapore, pp. 252-255, (IEEE) (2013)
• 2012
  • Ch. Dhanjal, N. Baskiotis, S. Clémençon, N. Usunier : “An Empirical Comparison of V-fold Penalisation and Cross Validation for Model Selection in Distribution-Free Regression”, (2012)
• 2011
  • S. Clémençon, N. Baskiotis, N. Usunier : “Calibrating SVMs with V-fold penalization”, Proceedings of Neural Information Processing Systems workshop on New Frontiers in Model Order Selection, Sierra Nevada, Spain (2011)
• 2010
  • E. Richard, N. Baskiotis, Th. Evgeniou, N. Vayatis : “Link Discovery using Graph Feature Tracking”, Neural Information Processing Systems, NIPS, vol. 23, Advances in Neural Information Processing Systems, Vancouver, Canada, pp. 1966-1974 (2010)