Outlier analysis is an important task in data mining and has attracted much attention in both research and applications. Previous work on outlier detection involves different type...
Wen Jin, Yuelong Jiang, Weining Qian, Anthony K. H...
Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step ...
Background: The study of genome rearrangements has become a mainstay of phylogenetics and comparative genomics. Fundamental in such a study is the median problem: given three geno...
Vaibhav Rajan, Andrew Wei Xu, Yu Lin, Krister M. S...
We study selectivity estimation techniques for set similarity queries. A wide variety of similarity measures for sets have been proposed in the past. In this work we concentrate o...
Marios Hadjieleftheriou, Xiaohui Yu, Nick Koudas, ...
We study how to best use crowdsourced relevance judgments learning to rank [1, 7]. We integrate two lines of prior work: unreliable crowd-based binary annotation for binary classi...