160 citations · 162 across the 3 of their papers we have counts for
4 papers
Optimal Stopping via Randomized Neural Networks
Calypso Herrera, Florian Krach, Pierre Ruyssen +1
This paper presents the benefits of using randomized neural networks instead of standard basis functions or deep neural networks to approximate the solutions of optimal stopping pr…
Denise: Deep Robust Principal Component Analysis for Positive Semidefinite Matrices
Calypso Herrera, Florian Krach, Anastasis Kratsios +2
The robust PCA of covariance matrices plays an essential role when isolating key explanatory features. The currently available methods for performing such a low-rank plus sparse de…
A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark
Xiaohua Zhai, Joan Puigcerver, Alexander Kolesnikov +14
Representation learning promises to unlock deep learning for the long tail of vision tasks without expensive labelled datasets. Yet, the absence of a unified evaluation for general…
Low-Rank plus Sparse Decomposition of Covariance Matrices using Neural Network Parametrization
Michel Baes, Calypso Herrera, Ariel Neufeld +1
This paper revisits the problem of decomposing a positive semidefinite matrix as a sum of a matrix with a given rank plus a sparse matrix. An immediate application can be found in…