5 papers
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…
Spiking Neural Networks and Online Learning: An Overview and Perspectives
Jesus L. Lobo, Javier Del Ser, Albert Bifet +1
Applications that generate huge amounts of data in the form of fast streams are becoming increasingly prevalent, being therefore necessary to learn in an online manner. These condi…
A heuristic approach for lactate threshold estimation for training decision-making: An accessible and easy to use solution for recreational runners
U. Etxegarai, E. Portillo, J. Irazusta +2
In this work, a heuristic as operational tool to estimate the lactate threshold and to facilitate its integration into the training process of recreational runners is proposed. To…
A Graph-Based Semi-Supervised k Nearest-Neighbor Method for Nonlinear Manifold Distributed Data Classification
Enmei Tu, Yaqian Zhang, Lin Zhu +2
Nearest Neighbors (NN) is one of the most widely used supervised learning algorithms to classify Gaussian distributed data, but it does not achieve good results when it is a…
Mapping Temporal Variables into the NeuCube for Improved Pattern Recognition, Predictive Modelling and Understanding of Stream Data
Enmei Tu, Nikola Kasabov, Jie Yang
This paper proposes a new method for an optimized mapping of temporal variables, describing a temporal stream data, into the recently proposed NeuCube spiking neural network archit…