In applying Hidden Markov Models to the analysis of massive data streams, it is often necessary to use an artificially reduced set of states; this is due in large part to the fac...
Pedro F. Felzenszwalb, Daniel P. Huttenlocher, Jon...
Adaptive sparse coding methods learn a possibly overcomplete set of basis functions, such that natural image patches can be reconstructed by linearly combining a small subset of t...
We derive efficient algorithms for both detecting and representing matchings in lopsided bipartite graphs; such graphs have so many nodes on one side that it is infeasible to repr...
Denis Charles, Max Chickering, Nikhil R. Devanur, ...
We present RDFGrowth, an algorithm that addresses a specific yet important scenario: large scale, end user targeted, metadata exchange P2P applications. In this scenario, peers per...
Giovanni Tummarello, Christian Morbidoni, Joackin ...
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...