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Our research focuses on a diverse number of theoretical and methodological areas finding applications in topics of Computer Vision, Data Mining, Signal Processing, Bioscience and Computational Intelligence, including:

  • Discriminant Learning
  • Graph-based analysis
  • Multi-view and multi-modal data analysis
  • Representation Learning
  • Neural Networks design and training
  • Kernel-based learning
  • Probabilistic analysis
  • Approximate learning for Big Data
  • Class-specific discrimination
  • Novelty detection
  • Data ranking and retrieval
  • Deep Learning