In this paper, we consider the multi-task sparse learning problem under the assumption that the dimensionality diverges with the sample size. The traditional l1/l2 multi-task lass...
Xi Chen, Jingrui He, Rick Lawrence, Jaime G. Carbo...
We give the first optimal algorithm for estimating the number of distinct elements in a data stream, closing a long line of theoretical research on this problem begun by Flajolet...
This article presents an online cluster using genetic algorithms to increase information retrieval efficiency. The Information Retrieval (IR) is based on the grouping of documents...
Data clustering represents an important tool in exploratory data analysis. The lack of objective criteria render model selection as well as the identification of robust solutions...
The emergence of the world-wide-web has led to an increased interest in methods for searching for information. A key characteristic of many of the online document collections is t...