We study the problem of clustering discrete probability distributions with respect to the Kullback-Leibler (KL) divergence. This problem arises naturally in many applications. Our...
By attempting to simultaneously partition both the rows (examples) and columns (features) of a data matrix, Co-clustering algorithms often demonstrate surprisingly impressive perf...
Vikas Sindhwani, Jianying Hu, Aleksandra Mojsilovi...
This paper develops new algorithms for coalition formation within multi-sensor networks tasked with performing widearea surveillance. Specifically, we cast this application as an ...
Viet Dung Dang, Rajdeep K. Dash, Alex Rogers, Nich...
In recent years realistic input models for geometric algorithms have been studied. The most important models introduced are fatness, low density, unclutteredness, and small simple...
Mark de Berg, Haggai David, Matthew J. Katz, Mark ...
: Partially-observable Markov decision processes provide a very general model for decision-theoretic planning problems, allowing the trade-offs between various courses of actions t...