The sparse data is becoming increasingly common and available in many real-life applications. However, relative little attention has been paid to effectively model the sparse data ...
While it is generally accepted that data warehouses and OLAP workloads are excellent applications for column-stores, this paper speculates that column-stores may well be suited fo...
Abstract. On Line Analytical Processing (OLAP) is a technology basically created to provide users with tools in order to explore and navigate into data cubes. Unfortunately, in hug...
Riadh Ben Messaoud, Omar Boussaid, Sabine Loudcher...
The current trend is for processors to deliver dramatic improvements in parallel performance while only modestly improving serial performance. Parallel performance is harvested th...
Sanjeev Kumar, Daehyun Kim, Mikhail Smelyanskiy, Y...
A "sparse" data set typically has hundreds or even thousands of attributes, but most objects have non-null values for only a small number of these attributes. A popular ...
Eric Chu, Jennifer L. Beckmann, Jeffrey F. Naughto...
In this paper, we propose the first formal privacy analysis of a data anonymization process known as the synthetic data generation, a technique becoming popular in the statistics c...
Ashwin Machanavajjhala, Daniel Kifer, John M. Abow...
This paper presents a framework for integrating multiple sensory data, sparse range data and dense depth maps from shape from shading in order to improve the 3D reconstruction of ...
Mostafa G.-H. Mostafa, Sameh M. Yamany, Aly A. Far...