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Birkbeck Knowledge Lab Seminar: Creating Ensembles of Generative Adversarial Network Discriminators for One-Class Classification

Venue: Online

We present an algorithm for one-class classification based on binary classification of the target class against synthetic samples. We use a process inspired by Generative Adversarial Networks (GANs) in order to both acquire synthetic samples and to build the one-class classifier. The first objective is achieved by leading the generator’s output into close vicinities of the target class region. For the second objective, we obtain a one-class classifier by generating an ensemble of discriminators obtained from the GAN’s training process. Our approach is tested on public domain datasets producing promising results when compared to other state-of-the-art methods.

Contact name:

  • Mihai Ermaliuc -

    Mihai Ermaliuc works as Data Science Manager at Accenture UK and is currently studying towards a PhD in Machine Learning at Goldsmiths, University of London. He has a background in Computer Science and Data Science. His research interests include generative models and their application on various topics, such as novelty detection.