We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
We consider learning models for object recognition from examples. Our method is motivated by systems that use the Hausdorff distance as a shape comparison measure. Typically an ob...
Abstract. The accurate prediction of Web navigation patterns has immense commercial value as the Web evolves into a primary medium for marketing and sales for many businesses. Ofte...
Malik Tahir Hassan, Khurum Nazir Junejo, Asim Kari...
Local bundle adjustment (LBA) has recently been introduced
to estimate the geometry of image sequences taken by
a calibrated camera. Its advantage over standard (global)
bundle ...
In this paper, we propose a new nonlinear dimensionality reduction algorithm by adopting regularized least-square criterion on local areas of the data distribution. We first propo...