Octavio Gonzalez-LugoAutoencoder architecture optimization by genetic programming.One of the main challenges in the development of neural networks is to determine the architecture. That means how the different layers are…Jan 29, 202047Jan 29, 202047
Octavio Gonzalez-LugoNeural network pruning with simulated annealingThe flexibility and adaptability of neural networks make them a great tool for several machine learning applications. However, neural…Apr 1, 2020111Apr 1, 2020111
Octavio Gonzalez-LugoAutomated feature engineering with evolutionary strategies.Inside a data set there different samples of a population, each sample contains several features that show us how each sample is unique…May 20, 202051May 20, 202051
Octavio Gonzalez-LugoParticle swarm for hyperparameter optimizationOn every machine learning algorithm that is applied to a data set, several hyperparameters need to be optimized to obtain the best…Jun 17, 20205Jun 17, 20205
Octavio Gonzalez-LugoIncorporating memory into feature selection for time series regression.From the weather to the stock market, the time series is one of the most common types of data sets that can be found. Also, there exist a…Aug 21, 20201Aug 21, 20201
Octavio Gonzalez-LugoHow to use clustering performance to improve the architecture of a variational autoencoderAn autoencoder is one of the many different special neural network designs, the main objective of an autoencoder is to learn how to return…Sep 19, 20201Sep 19, 20201
