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Found 2 papers, 1 papers with code
Recombination of Artificial Neural Networks
We propose a genetic algorithm (GA) for hyperparameter optimization of artificial neural networks which includes chromosomal crossover as well as a decoupling of parameters (i. e., weights and biases) from hyperparameters (e. g., learning rate, weight decay, and dropout) during sexual reproduction.
Spatter: A Tool for Evaluating Gather / Scatter Performance
This paper describes a new benchmark tool, Spatter, for assessing memory system architectures in the context of a specific category of indexed accesses known as gather and scatter.
Performance
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