—This paper describes a model of a hierarchical, heterogeneous knowledge-base. The proposed model consists of an associative level that is implemented by a Kanerva-like sparse di...
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...
Learning to rank is a new statistical learning technology on creating a ranking model for sorting objects. The technology has been successfully applied to web search, and is becom...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
Search queries applied to extract relevant information from the World Wide Web over a period of time may be denoted as continuous search queries. The improvement of continuous sea...
Many approximation algorithms have been presented in the last decades for hard search problems. The focus of this paper is on cryptographic applications, where it is desired to de...