5 citations · 14 across the 13 of their papers we have counts for
3 papers · 1 filter
Restarting Frank-Wolfe: Faster Rates Under Hölderian Error Bounds
Thomas Kerdreux, Alexandre d'Aspremont, Sebastian Pokutta
Conditional Gradient algorithms (aka Frank-Wolfe algorithms) form a classical set of methods for constrained smooth convex minimization due to their simplicity, the absence of proj…
Reconstructing Latent Orderings by Spectral Clustering
Antoine Recanati, Thomas Kerdreux, Alexandre d'Aspremont
Spectral clustering uses a graph Laplacian spectral embedding to enhance the cluster structure of some data sets. When the embedding is one dimensional, it can be used to sort the…
Frank-Wolfe with Subsampling Oracle
Thomas Kerdreux, Fabian Pedregosa, Alexandre d'Aspremont
We analyze two novel randomized variants of the Frank-Wolfe (FW) or conditional gradient algorithm. While classical FW algorithms require solving a linear minimization problem over…