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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Sep 1, 2020 - Python