6 citations · 9 across the 4 of their papers we have counts for
4 papers · 1 filter
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…
Como funciona o Deep Learning
Moacir Antonelli Ponti, Gabriel B. Paranhos da Costa
Deep Learning methods are currently the state-of-the-art in many problems which can be tackled via machine learning, in particular classification problems. However there is still l…
Computing the Shattering Coefficient of Supervised Learning Algorithms
Rodrigo Fernandes de Mello, Moacir Antonelli Ponti, Carlos Henrique Grossi Ferreira
The Statistical Learning Theory (SLT) provides the theoretical guarantees for supervised machine learning based on the Empirical Risk Minimization Principle (ERMP). Such principle…
Providing theoretical learning guarantees to Deep Learning Networks
Rodrigo Fernandes de Mello, Martha Dais Ferreira, Moacir Antonelli Ponti
Deep Learning (DL) is one of the most common subjects when Machine Learning and Data Science approaches are considered. There are clearly two movements related to DL: the first agg…