Labeling image collections is a tedious task, especially
when multiple labels have to be chosen for each image. In
this paper we introduce a new framework that extends state
of ...
Nicolas Loeff, Ali Farhadi, Ian Endres and David A...
Software quality prediction can be cast as a concept learning problem. In this paper, we discuss the full cycle of an application of Machine Learning to software quality predictio...
This paper describes a novel view-based learning algorithm for 3D object recognition from 2D images using a network of linear units. The SNoW learning architecture is a sparse netw...
This paper investigates a machine learning approach for temporally ordering and anchoring events in natural language texts. To address data sparseness, we used temporal reasoning ...
Inderjeet Mani, Marc Verhagen, Ben Wellner, Chong ...
: This paper deals with a progressive learning method for symbol recognition which improves its own recognition rate when new symbols are recognized in graphic documents. We propos...