5 citations · 5 across the 1 of their papers we have counts for
3 papers
cs.LG2020★ 5 cited
Beyond Signal Propagation: Is Feature Diversity Necessary in Deep Neural Network Initialization?
Yaniv Blumenfeld, Dar Gilboa, Daniel Soudry
Deep neural networks are typically initialized with random weights, with variances chosen to facilitate signal propagation and stable gradients. It is also believed that diversity…
cs.LG2019
Is Feature Diversity Necessary in Neural Network Initialization?
Yaniv Blumenfeld, Dar Gilboa, Daniel Soudry
Standard practice in training neural networks involves initializing the weights in an independent fashion. The results of recent work suggest that feature "diversity" at initializa…
stat.ML2019
A Mean Field Theory of Quantized Deep Networks: The Quantization-Depth Trade-Off
Yaniv Blumenfeld, Dar Gilboa, Daniel Soudry
Reducing the precision of weights and activation functions in neural network training, with minimal impact on performance, is essential for the deployment of these models in resour…