In this paper we make use of the idea that a robot can autonomously discover objects and learn their appearances by poking and prodding at interesting parts of a scene. In order t...
The use of local features in computer vision has shown to be promising. Local features have several advantages including invariance to image transformations, independence of the ba...
We present a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectru...
Approaches based on local features and descriptors are increasingly used for the task of object recognition due to their robustness with regard to occlusions and geometrical defor...
Kernel based nonlinear Feature Extraction (KFE) or dimensionality reduction is a widely used pre-processing step in pattern classification and data mining tasks. Given a positive...