Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
World Wide Web (WWW) is a vast source of information, the problem of information overload is more acute than ever. Due to noise in WWW, it is becoming hard to find usable informati...
We present a method to represent unstructured scalar fields at multiple levels of detail. Using a parallelizable classification algorithm to build a cluster hierarchy, we generate...
As organizations start to use data-intensive cluster computing systems like Hadoop and Dryad for more applications, there is a growing need to share clusters between users. Howeve...
Matei Zaharia, Dhruba Borthakur, Joydeep Sen Sarma...
Given a data matrix, the problem of finding dense/uniform sub-blocks in the matrix is becoming important in several applications. The problem is inherently combinatorial since th...