, Ère du Big Data et le besoin d'un traitement adapté, p.174

, Problèmes d'apprentissage artificiel non surpervisé, p.175

. , 177 Des matrices aléatoires structurées, une approche pour de l'apprentissage à grande échelle, p.177

, Apprentissage de codes compacts binaires de flux de données massives via le hashing hypercubique pour la recherche des plus proches voisins, p.178

. , Clustering de données massives à partir d'un arbre couvrant minimum

G. , Des matrices aléatoires structurées, une approche pour de l'apprentissage à grande échelle

. , Apprentissage de codes compacts binaires de flux de données massives via le hashing hypercubique pour la recherche des plus proches voisins

. , Clustering de données massives à partir d'un arbre couvrant minimum

, Sécurité de l'usage du sketching de graphe, p.186

. .. Passage-À-l'échelle-de-l'algorithme, , p.187

. , 5.1 Rappel des contributions et inscription dans le sujet, p.190

G. , Apprentissage de codes compacts binaires de flux de données massives via le hashing hypercubique pour la recherche des plus proches voisins 183

, Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS'17), vol.54, pp.20-22

, ? La contribution de la Section G.3 sur l'apprentissage de codes binaires compacts pour des données en grande dimension a été publiée à la Conférence Internationale de l'Acoutisque

A. Morvan, A. Souloumiac, C. Gouy-pailler, and J. Atif,

, Streaming Binary Sketching based on Subspace Tracking and Diagonal Uniformization Proceedings of the 2018 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.15-20

, Une extension de ce travail présentant des garanties théoriques supplémentaires avec une application au clustering préservant la vie privée différentielle a été publiée à la Conférence, ? L'approche sketching de graphe pour du clustering de flux de données massives a été publiée à la Conférence SIAM Data Mining (SDM) 2018, 2018.

A. Morvan, K. Choromanski, C. Gouy-pailler, and J. Atif, Graph sketching-based Space-efficient Data Clustering, Proceedings of the SIAM International Conference on DATA MINING (SDM'18), pp.3-4
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