Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
With proliferation of ubiquitous computing, digital access is facing an increasing risk since unauthorized client located at any place may intrude a local server. Location Based Ac...
The paper addresses the question whether it is possible for a machine to learn to distinguish and recognise famous musicians (concert pianists), based on their style of playing. We...
In Internet marketing, Web audience analysis is essential to understanding the visitors’ needs. However, the existing analysis tools fail to deliver summarized and conceptual me...
In this paper, we present a method that improves Japanese dependency parsing by using large-scale statistical information. It takes into account two kinds of information not consi...