7 citations · 12 across the 4 of their papers we have counts for
4 papers
Compressive K-means
Nicolas Keriven, Nicolas Tremblay, Yann Traonmilin +1
The Lloyd-Max algorithm is a classical approach to perform K-means clustering. Unfortunately, its cost becomes prohibitive as the training dataset grows large. We propose a compres…
Approximate search with quantized sparse representations
Himalaya Jain, Patrick Pérez, Rémi Gribonval +2
This paper tackles the task of storing a large collection of vectors, such as visual descriptors, and of searching in it. To this end, we propose to approximate database vectors by…
Separable Cosparse Analysis Operator Learning
Matthias Seibert, Julian Wörmann, Rémi Gribonval +1
The ability of having a sparse representation for a certain class of signals has many applications in data analysis, image processing, and other research fields. Among sparse repre…
Learning computationally efficient dictionaries and their implementation as fast transforms
Luc Le Magoarou, Rémi Gribonval
Dictionary learning is a branch of signal processing and machine learning that aims at finding a frame (called dictionary) in which some training data admits a sparse representatio…