29 citations · 33 across the 5 of their papers we have counts for
6 papers
Re-visiting Reservoir Computing architectures optimized by Evolutionary Algorithms
Sebastián Basterrech, Tarun Kumar Sharma
For many years, Evolutionary Algorithms (EAs) have been applied to improve Neural Networks (NNs) architectures. They have been used for solving different problems, such as training…
Tracking changes using Kullback-Leibler divergence for the continual learning
Sebastián Basterrech, Michal Woźniak
Recently, continual learning has received a lot of attention. One of the significant problems is the occurrence of \emph{concept drift}, which consists of changing probabilistic ch…
Prediction of Facebook Post Metrics using Machine Learning
Emmanuel Sam, Sergey Yarushev, Sebastián Basterrech +1
In this short paper, we evaluate the performance of three well-known Machine Learning techniques for predicting the impact of a post in Facebook. Social medias have a huge influenc…
Empirical Analysis of the Necessary and Sufficient Conditions of the Echo State Property
Sebastián Basterrech
The Echo State Network (ESN) is a specific recurrent network, which has gained popularity during the last years. The model has a recurrent network named reservoir, that is fixed du…
Single-sided Real-time PESQ Score Estimation
Sebastián Basterrech, Gerardo Rubino, Martín Varela
For several years now, the ITU-T's Perceptual Evaluation of Speech Quality (PESQ) has been the reference for objective speech quality assessment. It is widely deployed in commercia…
Echo State Queueing Network: a new reservoir computing learning tool
Sebastián Basterrech, Gerardo Rubino
In the last decade, a new computational paradigm was introduced in the field of Machine Learning, under the name of Reservoir Computing (RC). RC models are neural networks which a…