261 citations · 890 across the 15 of their papers we have counts for
4 papers · 1 filter
On the Long-Term Memory of Deep Recurrent Networks
Yoav Levine, Or Sharir, Alon Ziv +1
A key attribute that drives the unprecedented success of modern Recurrent Neural Networks (RNNs) on learning tasks which involve sequential data, is their ability to model intricat…
Sum-Product-Quotient Networks
Or Sharir, Amnon Shashua
We present a novel tractable generative model that extends Sum-Product Networks (SPNs) and significantly boosts their power. We call it Sum-Product-Quotient Networks (SPQNs), whose…
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…
On the Expressive Power of Overlapping Architectures of Deep Learning
Or Sharir, Amnon Shashua
Expressive efficiency refers to the relation between two architectures A and B, whereby any function realized by B could be replicated by A, but there exists functions realized by…