Sayak Mondal

HyperSpectrum geometry: a Riemannian hyperspherical framework for curvature-adaptive text classification

HyperSpectrum Geometry is proposed, a curvature metric-controlled hyperspherical manifold representation learning framework that combines a learnable global Riemannian metric tensor with normalized angular hyperspherical classification and suggests that learnable metric deformation constitutes a useful and underexplore...