We study the merging process when Kruskal's algorithm is run with random graphs as inputs. Our aim is to analyze this process when the underlying graph is the complete graph ...
Common document clustering algorithms utilize models that either divide a corpus into smaller clusters or gather individual documents into clusters. Hierarchical Agglomerative Clus...
Given a complete undirected graph, a cost function on edges and a degree bound B, the degree bounded network design problem is to find a minimum cost simple subgraph with maximum...
Yuk Hei Chan, Wai Shing Fung, Lap Chi Lau, Chun Ko...
We introduce a new, generic framework for private data analysis. The goal of private data analysis is to release aggregate information about a data set while protecting the privac...
EM algorithm is an important unsupervised clustering algorithm, but the algorithm has several limitations. In this paper, we propose a fast EM algorithm (FEMA) to address the limi...