The problem addressed by this research is the analysis and efficiency of neural networks, using a technique for network link pruning.
Results show the technique can significantly improve the efficiency of a neural network for a real application, both memory requirements and execution ...
Jun 18, 2020 · Our results show that DNN models evolve on unique, smooth trajectories in weight space which can be used to track DNN training progress.
Missing: Efficiency | Show results with:Efficiency
Sep 1, 2023 · This article aims to provide a comprehensive guide to neural network pruning techniques, offering insights into how they can help enhance deep learning ...
Abstract. Knowledge embedded in the weights of the artificial neural network can be used to improve the network structure, such as in network compression.
Network pruning methods are an effective approach to limit overparameterization of DNNs and to reduce the complexity of the network.
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Oct 22, 2024 · PDF | In this work, some ubiquitous neural networks are applied to model the landscape of a known problem function approximation.
Jun 28, 2017 · We show that feed-forward deep neural networks are capable of achieving strong classification performance and outperform shallow methods across diverse ...
Dec 20, 2023 · It is shown in this study that model simplification can benefit from investigating the network node, the most fundamental unit of neural networks, during ...
Missing: Investigation. | Show results with:Investigation.
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