479 citations · 1.5k across the 53 of their papers we have counts for
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cs.NE2016★ 23 cited
NoiseOut: A Simple Way to Prune Neural Networks
Mohammad Babaeizadeh, Paris Smaragdis, Roy H. Campbell
Neural networks are usually over-parameterized with significant redundancy in the number of required neurons which results in unnecessary computation and memory usage at inference…
cs.SD2016★ 3 cited
A Neural Network Alternative to Non-Negative Audio Models
Paris Smaragdis, Shrikant Venkataramani
We present a neural network that can act as an equivalent to a Non-Negative Matrix Factorization (NMF), and further show how it can be used to perform supervised source separation.…
cs.LG2016★ 172 cited
Bitwise Neural Networks
Minje Kim, Paris Smaragdis
Based on the assumption that there exists a neural network that efficiently represents a set of Boolean functions between all binary inputs and outputs, we propose a process for de…