Outlier mining in d-dimensional point sets is a fundamental and well studied data mining task due to its variety of applications. Most such applications arise in high-dimensional ...
In this paper a concern about the accuracy (as a function of parallelism) of a certain class of distributed learning algorithms is raised, and one proposed improvement is illustrat...
Lawrence O. Hall, Nitesh V. Chawla, Kevin W. Bowye...
Statistical machine translation to morphologically richer languages is a challenging task and more so if the source and target languages differ in word order. Current state-of-the...
The front end of many motion analysis algorithms is usually a process that generates bounding boxes around each moving object, roughly segmenting the objects from the background. ...
Parallel imaging methods provide accelerated multiple coil MR image acquisitions via reconstruction of sub-sampled kspace data. Currently, analytic comparison between different re...
William Scott Hoge, Bruno Madore, Walid E. Kyriako...