21 citations · 56 across the 13 of their papers we have counts for
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cs.LG2017★ 21 cited
Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions
Nadav Cohen, Or Sharir, Yoav Levine +3
The driving force behind convolutional networks - the most successful deep learning architecture to date, is their expressive power. Despite its wide acceptance and vast empirical…
cs.LG2017★ 8 cited
Boosting Dilated Convolutional Networks with Mixed Tensor Decompositions
Nadav Cohen, Ronen Tamari, Amnon Shashua
The driving force behind deep networks is their ability to compactly represent rich classes of functions. The primary notion for formally reasoning about this phenomenon is express…