Tree models are valuable tools for predictive modeling and data mining. Traditional tree-growing methodologies such as CART are known to suffer from problems including greediness,...
We present an improvement to Harvey and Ginsberg's limited discrepancy search algorithm, which eliminates much of the redundancy in the original, by generating each path from...
The Errors-in-Variables (EIV) model from statistics is often employed in computer vision thoughonlyrarely under this name. In an EIV model all the measurements are corrupted by no...
Most research in algorithms for geometric query problems has focused on their worstcase performance. However, when information on the query distribution is available, the alternat...
In this paper, we present a Dynamic Load Balancing (DLB) policy for problems characterized by a highly irregular search tree, whereby no reliable workload prediction is available....