54 citations · 62 across the 5 of their papers we have counts for
3 papers · 1 filter
Compressed Learning: A Deep Neural Network Approach
Amir Adler, Michael Elad, Michael Zibulevsky
Compressed Learning (CL) is a joint signal processing and machine learning framework for inference from a signal, using a small number of measurements obtained by linear projection…
SEBOOST - Boosting Stochastic Learning Using Subspace Optimization Techniques
Elad Richardson, Rom Herskovitz, Boris Ginsburg +1
We present SEBOOST, a technique for boosting the performance of existing stochastic optimization methods. SEBOOST applies a secondary optimization process in the subspace spanned b…
Spatially-Adaptive Reconstruction in Computed Tomography Based on Statistical Learning
Joseph Shtok, Michael Zibulevsky, Michael Elad
We propose a direct reconstruction algorithm for Computed Tomography, based on a local fusion of a few preliminary image estimates by means of a non-linear fusion rule. One such ru…