Scolarité M2 (sauf MIC, MIDS)
- Mme Chatoux
- bureau 5055
- 01 57 27 93 06
- Mme Prudlo
- bureau 5055
- 01 57 27 93 06
Algorithmique des données massives
3 ECTS, semester 1, 10 weeks
| Requirements | Machine Learning. Optimisation. Algorithmique avancée |
| Program requirements | CC+examen |
| Teacher | Stéphane Boucheron |
| Weekly hours | 2 h CM |
| Years | M2 Data Science (ouverture 2020) |
Syllabus
Usage des méthodes randomisées en traitement des données massives et en traitement des flots de données (streaming). Familiarisation avec Spark. Articulation estimation/optimisation
Contents
- Plus proches voisins en grande dimension.
- Locally sensitive hashing et au delà
- Applications aux données textuelles (Spark ML Feature Extraction)
- Compressed sensing
- Reconstruction parfaite des signaux parcimonieux par pénalisation $\ell_1$
- Algorithmes (LASSO, AMMD, Coordinate descent, ...)
- Données de streaming
- Échantillonnages
- Comptage approximatif (Hyperloglog, Spark SQL)
- Estimation robuste
- Enjeux
- Median of Means
- Relaxation SDP
Bibliography
- Arnold, T., & Tilton, L. (2015). Humanities data in R: exploring networks, geospatial data, images, and text. Springer.
- Bandeira, A. S. (2015). Ten lectures and forty-two open problems in the mathematics of data science. Lecture Notes.
- Blum, A., Hopcroft, J., & Kannan, R. (2016). Foundations of data science. Vorabversion eines Lehrbuchs.
- Boucheron, S., Lugosi, G., & Massart, P. (2013). Concentration inequalities: A nonasymptotic theory of independence. Oxford university press.
- Chambers, B., and Matei Z. (2018). Spark: the definitive guide: big data processing made simple. O'Reilly Media, Inc..
- Foucart, S., & Rauhut, H. (2013). A mathematical introduction to compressive sensing. Birkhäuser.
- Leskovec, J., Rajaraman, A., & Ullman, J. D. (2014). Mining of massive datasets. Cambridge university press.
- Lugosi, G. (2017). Lectures on Combinatorial Statistics. St. Flour.
- Moitra, A. (2018). Algorithmic aspects of machine learning. Cambridge University Press.
- Vershynin, R. (2018). High-dimensional probability: An introduction with applications in data science. Cambridge University Press.