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Found 4 papers, 1 papers with code
Context Matters: Adaptive Mutation for Grammars
This work proposes Adaptive Facilitated Mutation, a self-adaptive mutation method for Structured Grammatical Evolution (SGE), biologically inspired by the theory of facilitated variation.
Structured mutation inspired by evolutionary theory enriches population performance and diversity
Grammar-Guided Genetic Programming (GGGP) employs a variety of insights from evolutionary theory to autonomously design solutions for a given task.
Evolving Learning Rate Optimizers for Deep Neural Networks
Learning Rate optimizers are a set of such techniques that search for good values of learning rates.
AutoLR: An Evolutionary Approach to Learning Rate Policies
This work presents AutoLR, a framework that evolves Learning Rate Schedulers for a specific Neural Network Architecture using Structured Grammatical Evolution.
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