Abstract. Recently, we have proposed a novel method for the compression of time series based on mathematical models that explore dependencies between different time series. This r...
We consider the problem of Semi-supervised Learning (SSL) from general unlabeled data, which may contain irrelevant samples. Within the binary setting, our model manages to better...
Kaizhu Huang, Zenglin Xu, Irwin King, Michael R. L...
In this work, we study the problem of within-network relational learning and inference, where models are learned on a partially labeled relational dataset and then are applied to ...
This paper presents a data oriented approach to modeling the complex computing systems, in which an ensemble of correlation models are discovered to represent the system status. I...
OLAP (On-Line Analytical Processing) is an important notion in data analysis. Recently, more and more graph or networked data sources come into being. There exists a similar need ...