activity
20192022
collaborators

12 papers

cs.NE2022

A Novel Explainable Out-of-Distribution Detection Approach for Spiking Neural Networks

Aitor Martinez Seras, Javier Del Ser, Jesus L. Lobo +2

Research around Spiking Neural Networks has ignited during the last years due to their advantages when compared to traditional neural networks, including their efficient processing…

cs.LG2020

CURIE: A Cellular Automaton for Concept Drift Detection

Jesus L. Lobo, Javier Del Ser, Eneko Osaba +2

Data stream mining extracts information from large quantities of data flowing fast and continuously (data streams). They are usually affected by changes in the data distribution, g…

cs.AI2020

On the Transferability of Knowledge among Vehicle Routing Problems by using Cellular Evolutionary Multitasking

Eneko Osaba, Aritz D. Martinez, Jesus L. Lobo +2

Multitasking optimization is a recently introduced paradigm, focused on the simultaneous solving of multiple optimization problem instances (tasks). The goal of multitasking enviro…

cs.NE2020

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…

cs.LG2020

New Perspectives on the Use of Online Learning for Congestion Level Prediction over Traffic Data

Eric L. Manibardo, Ibai Laña, Jesus L. Lobo +1

This work focuses on classification over time series data. When a time series is generated by non-stationary phenomena, the pattern relating the series with the class to be predict…

cs.NE2020

Multifactorial Cellular Genetic Algorithm (MFCGA): Algorithmic Design, Performance Comparison and Genetic Transferability Analysis

Eneko Osaba, Aritz D. Martinez, Jesus L. Lobo +2

Multitasking optimization is an incipient research area which is lately gaining a notable research momentum. Unlike traditional optimization paradigm that focuses on solving a sing…