2 papers
cs.LG2021
Training Deep Networks from Zero to Hero: avoiding pitfalls and going beyond
Moacir Antonelli Ponti, Fernando Pereira dos Santos, Leo Sampaio Ferraz Ribeiro +1
Training deep neural networks may be challenging in real world data. Using models as black-boxes, even with transfer learning, can result in poor generalization or inconclusive res…
cs.CV2018
Unsupervised representation learning using convolutional and stacked auto-encoders: a domain and cross-domain feature space analysis
Gabriel B. Cavallari, Leonardo Sampaio Ferraz Ribeiro, Moacir Antonelli Ponti
A feature learning task involves training models that are capable of inferring good representations (transformations of the original space) from input data alone. When working with…