—The recent interest in outsourcing IT services onto the cloud raises two main concerns: security and cost. One task that could be outsourced is data mining. In VLDB 2007, Wong e...
This paper offers a local distributed algorithm for expectation maximization in large peer-to-peer environments. The algorithm can be used for a variety of well-known data mining...
Distribution data naturally arise in countless domains, such as meteorology, biology, geology, industry and economics. However, relatively little attention has been paid to data m...
— Learning Vector Quantization (LVQ) is a popular class of nearest prototype classifiers for multiclass classification. Learning algorithms from this family are widely used becau...
—We describe an efficient algorithm for releasing a provably private estimate of the degree distribution of a network. The algorithm satisfies a rigorous property of differenti...
—A large body of work has been devoted to address corporate-scale privacy concerns related to social networks. The main focus was on how to share social networks owned by organiz...
—Eigenvalue analysis is an important aspect in many data modeling methods. Unfortunately, the eigenvalues of the sample covariance matrix (sample eigenvalues) are biased estimate...
Anne Hendrikse, Luuk J. Spreeuwers, Raymond N. J. ...
—Mining temporal network models from discrete event streams is an important problem with applications in computational neuroscience, physical plant diagnostics, and human-compute...
—Knowledge discovery from scientific articles has received increasing attentions recently since huge repositories are made available by the development of the Internet and digit...
—We are now living in a world where information is growing and updating quickly. Knowledge can be acquired more efficiently with the help of automatic document summarization and...