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A Novel Loss Function Utilizing Wasserstein Distance to Reduce Subject-Dependent Noise for Generalizable Models in Affective Computing.

Nibraas KhanMahrukh TauseefRitam GhoshNilanjan Sarkar
Published in: HCI (12) (2024)
Keyphrases
  • loss function
  • affective computing
  • pairwise
  • learning to rank
  • artificial intelligence
  • learning algorithm
  • face recognition
  • support vector
  • distance measure
  • model selection