We consider the problem of joining massive datasets. We propose two techniques for minimizing disk I/O cost of join operations for both spatial and sequence data. Our techniques o...
In many applications, the expert interpretation of coclustering is easier than for mono-dimensional clustering. Co-clustering aims at computing a bi-partition that is a collection...
This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivat...
In dealing with large datasets the reduced support vector machine (RSVM) was proposed for the practical objective to overcome the computational difficulties as well as to reduce t...
In our research project named “Mega-Scale Computing Based on Low-Power Technology and Workload Modeling”, we have been developing a prototype cluster not based on ASIC or FPGA...