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TNN
2010
216views Management» more  TNN 2010»
13 years 3 months ago
Simplifying mixture models through function approximation
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
Kai Zhang, James T. Kwok
ALENEX
2008
142views Algorithms» more  ALENEX 2008»
13 years 10 months ago
Consensus Clustering Algorithms: Comparison and Refinement
Consensus clustering is the problem of reconciling clustering information about the same data set coming from different sources or from different runs of the same algorithm. Cast ...
Andrey Goder, Vladimir Filkov
CORR
2010
Springer
94views Education» more  CORR 2010»
13 years 7 months ago
When LP is the Cure for Your Matching Woes: Improved Bounds for Stochastic Matchings
Abstract Consider a random graph model where each possible edge e is present independently with some probability pe. Given these probabilities, we want to build a large/heavy match...
Nikhil Bansal, Anupam Gupta, Jian Li, Juliá...
NIPS
1998
13 years 9 months ago
Gradient Descent for General Reinforcement Learning
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
Leemon C. Baird III, Andrew W. Moore
AAAI
2011
12 years 8 months ago
On Expressing Value Externalities in Position Auctions
Externalities are recognized to exist in the sponsored search market, where two co-located ads compete for user attention. Existing work focuses on the effect of another ad on th...
Florin Constantin, Malvika Rao, Chien-Chung Huang,...