87 citations · 104 across the 6 of their papers we have counts for
4 papers · 1 filter
Position Paper on Dataset Engineering to Accelerate Science
Emilio Vital Brazil, Eduardo Soares, Lucas Villa Real +4
Data is a critical element in any discovery process. In the last decades, we observed exponential growth in the volume of available data and the technology to manipulate it. Howeve…
Towards Explainable Deep Neural Networks (xDNN)
Plamen Angelov, Eduardo Soares
In this paper, we propose an elegant solution that is directly addressing the bottlenecks of the traditional deep learning approaches and offers a clearly explainable internal arch…
A Self-Adaptive Synthetic Over-Sampling Technique for Imbalanced Classification
Xiaowei Gu, Plamen P Angelov, Eduardo Almeida Soares
Traditionally, in supervised machine learning, (a significant) part of the available data (usually 50% to 80%) is used for training and the rest for validation. In many problems, h…
Novelty Detection and Learning from Extremely Weak Supervision
Eduardo Soares, Plamen Angelov
In this paper we offer a method and algorithm, which make possible fully autonomous (unsupervised) detection of new classes, and learning following a very parsimonious training pri…