Abstract. We study the space complexity of randomized streaming algorithms that provide one-sided approximation guarantees; e.g., the algorithm always returns an overestimate of th...
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...
Abstract— Motivated by applications to sensor, peer-topeer and ad hoc networks, we study distributed asynchronous algorithms, also known as gossip algorithms, for computation and...
Stephen P. Boyd, Arpita Ghosh, Balaji Prabhakar, D...
For a large class of examples arising in statistical physics known as attractive spin systems (e.g., the Ising model), one seeks to sample from a probability distribution π on an...
Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clust...