Title

Long range dependence in Machine Learning

Abstract

La modélisation de la mémoire longue dans les données est un défi central auquel sont confrontées les applications modernes de l'apprentissage automatique aux séries temporelles. Nous présentons ici une manière de formaliser le concept de mémoire longue. Nous expliquons comment on peut estimer la mémoire longue dans la pratique et nous étudions son impact dans les algorithmes d'apprentissage automatique à la fois d'un point de vue empirique et théorique. Nous présentons deux applications : les systèmes de recommandation et les réseaux neuronaux séquence à séquence.

Bibliography

A. Burashnikova, M. Clausel, M.R. Amini, Y.Maximov, N. Dante, Recommender systems, when memory matters. European Conference on Information Retrieval (2022).

M. Clausel, F. Roueff, M.S. Taqqu, Large scale reduction principle and application to hypothesis testing. Electronic Journal of Statistics (2015)

A. Greaves-Tunnell, Z. Harchaoui A statistical investigation of long memory in language and music. International Conference on Machine Learning (2019)

M. Poli, S. Massaroli, E. Nguyen , D.Y. Fu, T. Dao, S. Baccus, Y. Bengio, S. Ermon, C. Ré Hyena hierarchy: Towards larger convolutional language models. arXiv preprint arXiv:2302.10866. 2023 Feb 21

Biography

Marianne Clausel (IECL, University of Lorraine) is a professor at the University of Lorraine, affiliated with IECL, since September 2017. She is also an external collaborator in the SiMul team at CRAN. From 2011 to 2017, she was an associate professor in the DAO team at Laboratoire Jean Kuntzmann (Université Grenoble Alpes). Since April 2019, Marianne has been a member of the Scientific Council of the French Machine Learning Society. From February 2022 to September 2023, she was a member of the Scientific Council of INSMI (Institut national des sciences mathématiques et des interactions), which is one of ten CNRS institutes. In 2018-2019, she was a member of the "Artificial Intelligence" Committee of the French National Agency (CES 23), participating in the selection of ANR projects in this field.  Since March 2018, Marianne has been an associate member of the APTIKAL team at the Grenoble Computer Science Laboratory, working mainly on machine learning and data analysis. She has worked with this group for five years. From September 2017 to August 2021, Marianne Clausel was a member of the AMIES Board of Directors. To this day, she is still involved in interactions with SMEs. From 2015 to 2021: Member of the Jury for the Agrégation Externe de Mathématiques. Marianne was involved in the selection procedures for secondary school mathematics teachers, notably for the "Modeling" oral test. From September 2019 to August 2021, she was also co-responsible, with F. Nicaise, for the "Probability and Statistics" option of the Agrégation Externe (pilot of option A in modeling).