100 citations · 110 across the 4 of their papers we have counts for
4 papers
Nonparametric adaptive active learning under local smoothness condition
Boris Ndjia Njike, Xavier Siebert
Active learning is typically used to label data, when the labeling process is expensive. Several active learning algorithms have been theoretically proved to perform better than th…
Deep matrix factorizations
Pierre De Handschutter, Nicolas Gillis, Xavier Siebert
Constrained low-rank matrix approximations have been known for decades as powerful linear dimensionality reduction techniques to be able to extract the information contained in lar…
K-NN active learning under local smoothness assumption
Boris Ndjia Njike, Xavier Siebert
There is a large body of work on convergence rates either in passive or active learning. Here we first outline some of the main results that have been obtained, more specifically i…
Near-Convex Archetypal Analysis
Pierre De Handschutter, Nicolas Gillis, Arnaud Vandaele +1
Nonnegative matrix factorization (NMF) is a widely used linear dimensionality reduction technique for nonnegative data. NMF requires that each data point is approximated by a conve…