We consider the question of how to store a value secretly on devices that continually leak information about their internal state to an external attacker. If the secret value is s...
Yevgeniy Dodis, Allison B. Lewko, Brent Waters, Da...
Traditional ranking mainly focuses on one type of data source, and effective modeling still relies on a sufficiently large number of labeled or supervised examples. However, in m...
Bo Wang, Jie Tang, Wei Fan, Songcan Chen, Zi Yang,...
Background: Cluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers...
Benjamin Georgi, Ivan Gesteira Costa, Alexander Sc...
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
We are building an interactive, visual text analysis tool that aids users in analyzing a large collection of text. Unlike existing work in text analysis, which focuses either on d...