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Found 2 essays matching the above criteria.

  1. 1. Evaluating Unsupervised Methods for Out-of-Distribution Detection on Semantically Similar Image Data

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Magnus Pierrau; [2021]
    Keywords : Out-of-distribution detection; anomaly detection; semantic similarity; image data; comparative evaluation; synthetic image data; Out-of-distribution detektion; anomali detektion; semantisk likhet; bilddata; jämförande utvärdering; syntetisk bilddata;

    Abstract : Out-of-distribution detection considers methods used to detect data that deviates from the underlying data distribution used to train some machine learning model. This is an important topic, as artificial neural networks have previously been shown to be capable of producing arbitrarily confident predictions, even for anomalous samples that deviate from the training distribution. READ MORE

  2. 2. Synthetic Meta-Learning: : Learning to learn real-world tasks with synthetic data

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Lukas Lundmark; [2019]
    Keywords : ;

    Abstract : Meta-learning is an approach to machine learning that teaches models how to learn new tasks with only a handful of examples. However, meta-learning requires a large labeled dataset during its initial meta-learning phase, which restricts what domains meta-learning can be used in. READ MORE