Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
We prove that for any positive integer k, there is a constant ck such that a randomly selected set of cknk log n Boolean vectors with high probability supports a balanced k-wise i...
We describe a Markov chain Monte Carlo (MCMC)-based algorithm for sampling solutions to mixed Boolean/integer constraint problems. The focus of this work differs in two points from...
Skyline computation is widely used in multi-criteria decision making. As research in uncertain databases draws increasing attention, skyline queries with uncertain data have also ...
Partitions of sequential data exist either per se or as a result of sequence segmentation algorithms. It is often the case that the same timeline is partitioned in many different ...