: This review presents empirical researchers with recent advances in causal inference, and stresses the paradigmatic shifts that must be undertaken in moving from traditional stati...
Learning theory has largely focused on two main learning scenarios. The first is the classical statistical setting where instances are drawn i.i.d. from a fixed distribution and...
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
We present a comprehensive treatment of 3D object tracking by posing it as a nonlinear state estimation problem. The measurements are derived using the outputs of shape-encoded fi...
The paper introduces a new framework for feature learning in classification motivated by information theory. We first systematically study the information structure and present a n...
We describe a new invariant-based data model for image databases under our approach for shape-based retrieval. The data model relies on contours description of the image shape, an...