We present a Bayesian clustering algorithm for multivariate time series. A clustering is regarded as a probabilistic model in which the unknown auto-correlation structure of a tim...
We give a simple framework which is an alternative to the celebrated and widely used shifting strategy of Hochbaum and Maass [J. ACM, 1985] which has yielded efficient algorithms ...
We study the mergeability of data summaries. Informally speaking, mergeability requires that, given two summaries on two data sets, there is a way to merge the two summaries into ...
Pankaj K. Agarwal, Graham Cormode, Zengfeng Huang,...
Classification trees are widely used in the machine learning and data mining communities for modeling propositional data. Recent work has extended this basic paradigm to probabili...
Jennifer Neville, David Jensen, Lisa Friedland, Mi...
In multi-issue negotiations, issues may be negotiated independently or not. In the latter case, the utility associated with one issue depends on the value of another. These issue d...
Koen V. Hindriks, Catholijn M. Jonker, Dmytro Tykh...