A Simple Parametric Classification Baseline for Generalized Category Discovery

@article{Wen2022ASP,
  title={A Simple Parametric Classification Baseline for Generalized Category Discovery},
  author={Xin Wen and Bingchen Zhao and Xiaojuan Qi},
  journal={ArXiv},
  year={2022},
  volume={abs/2211.11727}
}
Generalized category discovery (GCD) is a problem setting where the goal is to discover novel categories within an unlabelled dataset using the knowledge learned from a set of labelled samples. Recent works in GCD argue that a non-parametric classifier formed using semi-supervised k means can outperform strong baselines which use parametric classifiers as it can alleviate the over-fitting to seen categories in the labelled set. In this paper, we revisit the reason that makes previous parametric… 

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