Binary segmentation, a problem of extracting foreground objects from the background, often arises in medical imaging and document processing. Popular existing solutions include Ex...
This paper presents an e cient scheme for a neinvariant object recognition. A ne invariance is obtained by a representation which is based on a new sampling con guration in the fr...
In high-dimensional and complex metric spaces, determining the nearest neighbor (NN) of a query object ? can be a very expensive task, because of the poor partitioning operated by...
In machine learning problems with tens of thousands of features and only dozens or hundreds of independent training examples, dimensionality reduction is essential for good learni...
In this paper, we investigate how deviation in evaluation activities may reveal bias on the part of reviewers and controversy on the part of evaluated objects. We focus on a `data...