We consider the task of performing anomaly detection in highly noisy multivariate data. In many applications involving real-valued time-series data, such as physical sensor data a...
We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or transductive inference. A principled approach to sem...
Dengyong Zhou, Olivier Bousquet, Thomas Navin Lal,...
In recent years, privacy preserving data mining has become an important problem because of the large amount of personal data which is tracked by many business applications. In many...
Data collected using traceroute-based algorithms underpins research into the Internet’s router-level topology, though it is possible to infer false links from this data. One sou...
Matthew J. Luckie, Amogh Dhamdhere, kc claffy, Dav...
This paper is concerned with the reconstruction of perfect phylogenies from binary character data with missing values, and related problems of inferring complete haplotypes from h...