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

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2016

Modern computer vision is all about the possession of powerful image representations. Deeper and deeper convolutional neural…

2012

Domain adaptation algorithms that handle shifts in the distribution between training and testing data are receiving much…

2005

The Compressed Sensing framework aims to recover a sparse signal from a small set of projections onto random vec tors; the…

2004

Our objective is to learn representations for the shape and the appearance of moving (dynamic) objects that supports tasks such…

2003

The analysis of blood flow patterns and the interaction between salient topological flow features and cardiovascular structure…

2001

A new strong mathematically rigorous and numerically effective method for solving the boundary value problem of scalar (for…

1999

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

1995

Soit (M 4n , g, Q) n>1, une variete Kahler-quaternionienne a courbure scalaire K positive et differente de l'espace projectif…

1993

An edge detection and surface reconstruction algorithm in which the smoothness is controlled spatially over the image space is…

1952