Evolutionary Neural Network Optimization
- PyTorch
- evolutionary algorithms
- optimization
- AutoML
What it is
An experiment in using evolutionary algorithms to optimize neural-network training hyperparameters (e.g. learning rate, momentum).
It implements both single-objective and multi-objective evolution — the multi-objective variant searches for a Pareto front trading off final accuracy against time-to-target-accuracy. Candidates are evaluated with partial training, then the best is fully trained and logged. Includes baseline comparisons and plotting utilities across multiple epoch budgets.
Stack
Python · PyTorch · custom evolutionary/genetic operators · Pareto-front selection