2 papers
cs.LG2023
Manifold Regularization for Memory-Efficient Training of Deep Neural Networks
Shadi Sartipi, Edgar A. Bernal
One of the prevailing trends in the machine- and deep-learning community is to gravitate towards the use of increasingly larger models in order to keep pushing the state-of-the-art…
cs.IT2014
Two algorithms for compressed sensing of sparse tensors
Shmuel Friedland, Qun Li, Dan Schonfeld +1
Compressed sensing (CS) exploits the sparsity of a signal in order to integrate acquisition and compression. CS theory enables exact reconstruction of a sparse signal from relative…