Co-evolving Recurrent Neural Networks and their Hyperparameters with Simplex Hyperparameter Optimization.
Amit Dilip KiniSwaraj Sambhaji YadavAditya Shankar ThakurAkshar Bajrang AwariZimeng LyuTravis DesellPublished in: GECCO Companion (2023)
Keyphrases
- hyperparameters
- recurrent neural networks
- model selection
- grid search
- cross validation
- bayesian inference
- bayesian framework
- closed form
- random sampling
- parameter optimization
- support vector
- prior information
- gaussian process
- em algorithm
- gaussian processes
- noise level
- maximum a posteriori
- maximum likelihood
- sample size
- incremental learning
- feed forward
- neural network
- echo state networks
- incomplete data
- random forest
- recurrent networks
- missing values
- support vector machine
- prior knowledge
- artificial neural networks
- active learning
- lower bound
- machine learning
- probabilistic model
- parameter settings
- higher order
- data sets