Learning problems form an important category of computational tasks that generalizes many of the computations researchers apply to large real-life data sets. We ask: what concept ...
Shiva Prasad Kasiviswanathan, Homin K. Lee, Kobbi ...
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
In this paper we describe a method for estimating curvature of elongated structures in images. The curvature estimation is performed on an invertible orientation score, which is a...
Erik Franken, Remco Duits, Bart M. ter Haar Romeny
We consider the problem of recognizing an object from its silhouette. We focus on the case in which the camera translates, and rotates about a known axis parallel to the image, suc...
This paper addresses the issue of text normalization, an important yet often overlooked problem in natural language processing. By text normalization, we mean converting ‘inform...
Conghui Zhu, Jie Tang, Hang Li, Hwee Tou Ng, Tieju...