54 citations · 92 across the 6 of their papers we have counts for
3 papers · 2 filters
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…
A Deep Learning Approach to Block-based Compressed Sensing of Images
Amir Adler, David Boublil, Michael Elad +1
Compressed sensing (CS) is a signal processing framework for efficiently reconstructing a signal from a small number of measurements, obtained by linear projections of the signal.…