Our new paper Quantile–Quantile Embedding for Distribution Transformation and Manifold Embedding (Ghojogh et al., 2021) on a novel method for shaping distributions using a new twist on classic quantile-quantile plotting methods has been accepted for publication in the Elsevier journal Machine Learning with Applications (MLWA).
This paper comes out of the Manifold Learning research topic in out lab led by postdoc Benyamin Ghojogh and was one of the components of his recent completed PhD thesis (Ghojogh, 2021) here in the lab.
- QQEQuantile–Quantile Embedding for distribution transformation and manifold embedding with ability to choose the embedding distributionMachine Learning with Applications (MLWA). 6, 2021.
- Phd ThesisData Reduction Algorithms in Machine Learning and Data ScienceFeb, 2021.