Manifold regularization

In machine learning, Manifold regularization is a technique for using the shape of a dataset to constrain the functions that should be learned on…

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.

2014

In this paper, we prove that if there exists a second order symmetric parallel tensor on an almost Kenmotsu manifold $(M^{2n+1…

2009

In this paper we consider nonlinear ill-posed problems with piecewise constant or strongly varying solutions. A class of…

2008

Head pose estimation has been an integral problem in the study of face recognition systems and human-computer interfaces, as part…

2008

An image-set based face recognition algorithm is proposed that exploits the full geometrical interpretation of Canonical…

2006

Inferring 3D body pose as well as viewpoint from a single silhouette image is a challenging problem. We present a new generative…

2003

We present a pseudopotential calculation of the single particle and excitonic spectrum of CdSe nanocrystals. We find that in the…

1999

Featuring exactness and robustness, standard sliding mode may also cause the so-called chattering effect. Having hidden the…

1997

Witt's theorem on the extension of H-isometries to H-unitary matrices with respect to the scalar product generated by a self…

1996

An algorithm is described for computing fixed points on a Grassmannian manifold. The method can be applied in the more general…

1980

Introduction. Minimal immersions of spheres into a sphere have been completely determined by do Carmo and Wallach [2]. Let H be…