Overparameterization and overfitting are common concerns when designing and training deep neural networks. Network pruning is an effective strategy used to reduce or limit the network complexity, but often suffers from time and computational intensive procedures to identify the most important connections and best performing hyperparameters. We s…
machine-learning
sparsity
ai
tensorflow
keras
python3
image-classification
automl
l1-regularization
network-compression
unstructured-weight-pruning
multiobjective-learning
soft-pruning
stochastic-multi-gradient
dichotomic-serach
dense-layers
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Updated
Sep 1, 2020 - Python