24 citations · 38 across the 12 of their papers we have counts for
Showing 2018Show all
3 papers · 1 filter
cs.LG2018★ 2 cited
Compressive Classification (Machine Learning without learning)
Vincent Schellekens, Laurent Jacques
Compressive learning is a framework where (so far unsupervised) learning tasks use not the entire dataset but a compressed summary (sketch) of it. We propose a compressive learning…
cs.IT2018★ 2 cited
Taking the edge off quantization: projected back projection in dithered compressive sensing
Chunlei Xu, Vincent Schellekens, Laurent Jacques
Quantized compressive sensing (QCS) deals with the problem of representing compressive signal measurements with finite precision representation, i.e., a mandatory process in any pr…
cs.LG2018★ 24 cited
Quantized Compressive K-Means
Vincent Schellekens, Laurent Jacques
The recent framework of compressive statistical learning aims at designing tractable learning algorithms that use only a heavily compressed representation-or sketch-of massive data…