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» Optimal sampling from distributed streams
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UAI
2004
13 years 10 months ago
PAC-learning Bounded Tree-width Graphical Models
We show that the class of strongly connected graphical models with treewidth at most k can be properly efficiently PAC-learnt with respect to the Kullback-Leibler Divergence. Prev...
Mukund Narasimhan, Jeff A. Bilmes
TNN
2010
154views Management» more  TNN 2010»
13 years 3 months ago
Discriminative semi-supervised feature selection via manifold regularization
We consider the problem of semi-supervised feature selection, where we are given a small amount of labeled examples and a large amount of unlabeled examples. Since a small number ...
Zenglin Xu, Irwin King, Michael R. Lyu, Rong Jin
SODA
2000
ACM
132views Algorithms» more  SODA 2000»
13 years 10 months ago
Expected-case complexity of approximate nearest neighbor searching
Most research in algorithms for geometric query problems has focused on their worstcase performance. However, when information on the query distribution is available, the alternat...
Sunil Arya, Ho-Yam Addy Fu
CORR
2000
Springer
91views Education» more  CORR 2000»
13 years 8 months ago
Algorithmic Theories of Everything
The probability distribution P from which the history of our universe is sampled represents a theory of everything or TOE. We assume P is formally describable. Since most (uncount...
Jürgen Schmidhuber
NECO
2011
13 years 3 months ago
Least Squares Estimation Without Priors or Supervision
Selection of an optimal estimator typically relies on either supervised training samples (pairs of measurements and their associated true values), or a prior probability model for...
Martin Raphan, Eero P. Simoncelli