— We study hybrid search schemes for unstructured peer-to-peer networks. We quantify performance in terms of number of hits, network overhead, and response time. Our schemes comb...
Many ensemble methods, such as Bagging, Boosting, Random Forest, etc, have been proposed and widely used in real world applications. Some of them are better than others on noisefre...
We present a new series of distributed constraint satisfaction algorithms, the distributed breakout algorithms, which is inspired by local search algorithms for solving the constr...
Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clust...
Iterative improvement partitioning algorithms such as the FM algorithm of Fiduccia and Mattheyses 8 , the algorithm of Krishnamurthy 13 , and Sanchis's extensions of these al...
Lars W. Hagen, Dennis J.-H. Huang, Andrew B. Kahng