4 papers
AiGAS-dEVL-RC: An Adaptive Growing Neural Gas Model for Recurrently Drifting Unsupervised Data Streams
Maria Arostegi, Miren Nekane Bilbao, Jesus L. Lobo +1
Concept drift and extreme verification latency pose significant challenges in data stream learning, particularly when dealing with recurring concept changes in dynamic environments…
On the Post-hoc Explainability of Deep Echo State Networks for Time Series Forecasting, Image and Video Classification
Alejandro Barredo Arrieta, Sergio Gil-Lopez, Ibai Laña +2
Since their inception, learning techniques under the Reservoir Computing paradigm have shown a great modeling capability for recurrent systems without the computing overheads requi…
Deep Echo State Networks for Short-Term Traffic Forecasting: Performance Comparison and Statistical Assessment
Javier Del Ser, Ibai Lana, Eric L. Manibardo +5
In short-term traffic forecasting, the goal is to accurately predict future values of a traffic parameter of interest occurring shortly after the prediction is queried. The activit…
Beamwidth Optimization in Millimeter Wave Small Cell Networks with Relay Nodes: A Swarm Intelligence Approach
Cristina Perfecto, Javier Del Ser, Muhammad Ikram Ashraf +2
Millimeter wave (mmWave) communications have been postulated as one of the most disruptive technologies for future 5G systems. Among mmWave bands the 60-GHz radio technology is spe…