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Distinction Maximization Loss: Efficiently Improving Classification Accuracy, Uncertainty Estimation, and Out-of-Distribution Detection Simply Replacing the Loss and Calibrating.

David MacêdoCleber ZanchettinTeresa Bernarda Ludermir
Published in: CoRR (2022)
Keyphrases
  • improving classification accuracy
  • objective function
  • data sets
  • feature selection
  • feature vectors
  • probabilistic model
  • classification accuracy
  • probability distribution
  • object detection
  • maximum likelihood