Optimizing Hyperparameters in CNNs using Bilevel Programming in Time Series Data
This is an incremental idea for improving CNN performance in time series prediction, though it lacks experimental validation.
The paper tackles hyperparameter optimization in CNNs for time series prediction by proposing a bilevel programming approach, but no concrete results or numbers are provided.
Hyperparameter optimization has remained a central topic within the machine learning community due to its ability to produce state-of-the-art results. With the recent interest growing in the usage of CNNs for time series prediction, we propose the notion of optimizing Hyperparameters in CNNs for the purpose of time series prediction. In this position paper, we give away the idea of modeling the concerned hyperparameter optimization problem using bilevel programming.