We present a new approximation method called value extrapolation for Markov processes with large or infinite state spaces. The method can be applied for calculating any performan...
We show that approximating the shortest vector problem (in any p norm) to within any constant factor less than p 2 is hard for NP under reverse unfaithful random reductions with i...
—We apply large deviations theory to study asymptotic performance of running consensus distributed detection in sensor networks. Running consensus is a stochastic approximation t...
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...
We examine the problem of retrieving the top-m ranked items from a large collection, randomly distributed across an n-node system. In order to retrieve the top m overall, we must ...