6 citations · 7 across the 2 of their papers we have counts for
2 papers
cs.LG2020★ 1 cited
Understanding Boolean Function Learnability on Deep Neural Networks: PAC Learning Meets Neurosymbolic Models
Marcio Nicolau, Anderson R. Tavares, Zhiwei Zhang +4
Computational learning theory states that many classes of boolean formulas are learnable in polynomial time. This paper addresses the understudied subject of how, in practice, such…
cs.LG2018★ 6 cited
Fusarium Damaged Kernels Detection Using Transfer Learning on Deep Neural Network Architecture
Márcio Nicolau, Márcia Barrocas Moreira Pimentel, Casiane Salete Tibola +2
The present work shows the application of transfer learning for a pre-trained deep neural network (DNN), using a small image dataset ( 12,000) on a single workstation with…