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» Information Theory, Inference, and Learning Algorithms
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LPNMR
2009
Springer
14 years 2 months ago
The Complexity of Circumscriptive Inference in Post's Lattice
Circumscription is one of the most important formalisms for reasoning with incomplete information. It is equivalent to reasoning under the extended closed world assumption, which a...
Michael Thomas
EMNLP
2009
13 years 5 months ago
Multi-Class Confidence Weighted Algorithms
The recently introduced online confidence-weighted (CW) learning algorithm for binary classification performs well on many binary NLP tasks. However, for multi-class problems CW l...
Koby Crammer, Mark Dredze, Alex Kulesza
SIGECOM
2006
ACM
184views ECommerce» more  SIGECOM 2006»
14 years 1 months ago
Computing pure nash equilibria in graphical games via markov random fields
We present a reduction from graphical games to Markov random fields so that pure Nash equilibria in the former can be found by statistical inference on the latter. Our result, wh...
Constantinos Daskalakis, Christos H. Papadimitriou
ICASSP
2011
IEEE
12 years 11 months ago
Sparse coding and dictionary learning based on the MDL principle
The power of sparse signal coding with learned overcomplete dictionaries has been demonstrated in a variety of applications and fields, from signal processing to statistical infe...
Ignacio Ramírez, Guillermo Sapiro
FTML
2008
185views more  FTML 2008»
13 years 8 months ago
Graphical Models, Exponential Families, and Variational Inference
The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...
Martin J. Wainwright, Michael I. Jordan