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05/12/2022
Distinction Maximization Loss: Efficiently Improving Classification Accuracy, Uncertainty Estimation, and Out-of-Distribution Detection Simply Replacing the Loss and Calibratin
Building robust deterministic neural networks remains a challenge. On th...
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08/02/2021
Metodos de Agrupamentos em dois Estagios
This work investigates the use of two-stage clustering methods. Four tec...
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07/29/2021
Otimizacao de pesos e funcoes de ativacao de redes neurais aplicadas na previsao de series temporais
Neural Networks have been applied for time series prediction with good e...
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07/18/2021
Otimizacao de Redes Neurais atraves de Algoritmos Geneticos Celulares
This works proposes a methodology to searching for automatically Artific...
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07/10/2021
Meta-aprendizado para otimizacao de parametros de redes neurais
The optimization of Artificial Neural Networks (ANNs) is an important ta...
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07/05/2021
Uso de GSO cooperativos com decaimentos de pesos para otimizacao de redes neurais
Training of Artificial Neural Networks is a complex task of great import...
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05/30/2021
Improving Entropic Out-of-Distribution Detection using Isometric Distances and the Minimum Distance Score
Current out-of-distribution detection approaches usually present special...
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02/17/2021
Training Aware Sigmoidal Optimizer
Proper optimization of deep neural networks is an open research question...
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10/13/2020
Similarity Based Stratified Splitting: an approach to train better classifiers
We propose a Similarity-Based Stratified Splitting (SBSS) technique, whi...
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06/07/2020