Already purchased this program?
Login to View
This video program is a part of the Premium package:
Ssgd: Sparsity-Promoting Stochastic Gradient Descent Algorithm For Unbiased Dnn Pruning
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Ssgd: Sparsity-Promoting Stochastic Gradient Descent Algorithm For Unbiased Dnn Pruning
While deep neural networks (DNNs) have achieved state-of-the-art results in many fields, they are typically over-parameterized. Parameter redundancy, in turn, leads to inefficiency. Sparse signal recovery (SSR) techniques, on the other hand, find compact
While deep neural networks (DNNs) have achieved state-of-the-art results in many fields, they are typically over-parameterized. Parameter redundancy, in turn, leads to inefficiency. Sparse signal recovery (SSR) techniques, on the other hand, find compact