Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
We describe an online approach to learn non-linear motion patterns and robust appearance models for multi-target tracking in a tracklet association framework. Unlike most previous...
We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine vision tasks. The appro...
We compare the relative utility of different automatically computable linguistic feature sets for modeling student learning in computer dialogue tutoring. We use the PARADISE frame...
Katherine Forbes-Riley, Diane J. Litman, Amruta Pu...
This paper presents a novel method for reconstructing a 3D human body pose from stereo image sequences based on a top-down learning method. However, it is inefficient to build a ...