: Most of Knowledge Discovery in Database (KDD) systems are integrating efficient Machine Learning techniques. In fact issues in Machine Learning and KDD are very close allowing fo...
Jean-Daniel Zucker, Vincent Corruble, J. Thomas, G...
Constructing Haar wavelet synopses under a given approximation error has many real world applications. In this paper, we take a novel approach towards constructing unrestricted Ha...
Chaoyi Pang, Qing Zhang, David P. Hansen, Anthony ...
Covariate shift is a situation in supervised learning where training and test inputs follow different distributions even though the functional relation remains unchanged. A common...
Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen...
This paper describes nonparametric Bayesian treatments for analyzing records containing occurrences of items. The introduced model retains the strength of previous approaches that...
This paper describes the development of a software tool for detection of vulnerabilities in networked systems, using public available security resources. Our tool builds is knowle...