We present new algorithms for computing approximate quantiles of large datasets in a single pass. The approximation guarantees are explicit, and apply without regard to the value ...
Gurmeet Singh Manku, Sridhar Rajagopalan, Bruce G....
We introduce a model of uncertainty where documents are not uniquely identified in a reference network, and some links may be incorrect. It generalizes the probabilistic approach ...
Abstract. This paper addresses the problem of probabilistically modeling 3D human motion for synthesis and tracking. Given the high dimensional nature of human motion, learning an ...
Estimating the result size of complex queries that involve selection on multiple attributes and the join of several relations is a difficult but fundamental task in database query...
Motivated by the increasing need to analyze complex, uncertain multidimensional data this paper proposes probabilistic OLAP queries that are computed using probability distributio...
Igor Timko, Curtis E. Dyreson, Torben Bach Pederse...