Search Results for author:
Found 4 papers, 1 papers with code
Intelligent gradient amplification for deep neural networks
Deep learning models offer superior performance compared to other machine learning techniques for a variety of tasks and domains, but pose their own challenges.
PK-GCN: Prior Knowledge Assisted Image Classification using Graph Convolution Networks
Deep learning has gained great success in various classification tasks.
Deep Neural Networks with Short Circuits for Improved Gradient Learning
Deep neural networks have achieved great success both in computer vision and natural language processing tasks.
Efficient Hyperparameter Optimization in Deep Learning Using a Variable Length Genetic Algorithm
However, traditional genetic algorithms with fixed-length chromosomes may not be a good fit for optimizing deep learning hyperparameters, because deep learning models have variable number of hyperparameters depending on the model depth.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
