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» Genericity, Randomness, and Polynomial-Time Approximations
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UAI
2004
13 years 11 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
CVPR
2006
IEEE
14 years 12 months ago
Solving Markov Random Fields using Second Order Cone Programming Relaxations
This paper presents a generic method for solving Markov random fields (MRF) by formulating the problem of MAP estimation as 0-1 quadratic programming (QP). Though in general solvi...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
PODS
2011
ACM
220views Database» more  PODS 2011»
13 years 23 days ago
Maximizing conjunctive views in deletion propagation
In deletion propagation, tuples from the database are deleted in order to reflect the deletion of a tuple from the view. Such an operation may result in the (often necessary) del...
Benny Kimelfeld, Jan Vondrák, Ryan Williams
ISSAC
2007
Springer
93views Mathematics» more  ISSAC 2007»
14 years 4 months ago
Approximate bivariate factorization: a geometric viewpoint
We briefly present and analyze, from a geometric viewpoint, strategies for designing algorithms to factor bivariate approximate polynomials in   [x, y]. Given a composite polyno...
André Galligo, Mark van Hoeij
UAI
1998
13 years 11 months ago
Large Deviation Methods for Approximate Probabilistic Inference
We study two-layer belief networks of binary random variables in which the conditional probabilities Pr childjparents depend monotonically on weighted sums of the parents. In larg...
Michael J. Kearns, Lawrence K. Saul