Kernelized sorting is an approach for matching objects from two sources (or domains) that does not require any prior notion of similarity between objects across the two sources. U...
Jagadeesh Jagarlamudi, Seth Juarez, Hal Daum&eacut...
This paper explores the use of innovative kernels based on syntactic and semantic structures for a target relation extraction task. Syntax is derived from constituent and dependen...
Truc-Vien T. Nguyen, Alessandro Moschitti, Giusepp...
As a well known fixed-point iteration algorithm for kernel
density mode-seeking, Mean-Shift has attracted wide attention
in pattern recognition field. To date, Mean-Shift algorit...
Abstract. Many supervised and unsupervised learning algorithms depend on the choice of an appropriate distance metric. While metric learning for supervised learning tasks has a lon...
In this paper, we discuss fuzzy classifiers based on Kernel Discriminant Analysis (KDA) for two-class problems. In our method, first we employ KDA to the given training data and ca...