Selecting a set of good and diverse base classifiers is essential for building multiple classifier systems. However, almost all commonly used procedures for selecting such base cla...
This paper describes a parameter estimation method for multi-label classification that does not rely on approximate inference. It is known that multi-label classification involvin...
Most recent class-level object recognition systems work with visual words, i.e., vector quantized local descriptors. In this paper we examine the feasibility of a dataindependent ...
Subgraph patterns are widely used in graph classification, but their effectiveness is often hampered by large number of patterns or lack of discrimination power among individual p...
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...