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» Computational Complexity of Probabilistic Disambiguation
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CORR
2012
Springer
170views Education» more  CORR 2012»
13 years 7 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson
NDSS
2008
IEEE
15 years 6 months ago
Usable PIR
In [22] we showed that existing single-server computational private information retrieval (PIR) protocols for the purpose of preserving client access patterns leakage are orders o...
Peter Williams, Radu Sion
BMCBI
2005
169views more  BMCBI 2005»
14 years 11 months ago
Genetic interaction motif finding by expectation maximization - a novel statistical model for inferring gene modules from synthe
Background: Synthetic lethality experiments identify pairs of genes with complementary function. More direct functional associations (for example greater probability of membership...
Yan Qi 0003, Ping Ye, Joel S. Bader
STOC
2004
ACM
157views Algorithms» more  STOC 2004»
16 years 19 hour ago
Derandomizing homomorphism testing in general groups
The main result of this paper is a near-optimal derandomization of the affine homomorphism test of Blum, Luby and Rubinfeld (Journal of Computer and System Sciences, 1993). We sho...
Amir Shpilka, Avi Wigderson
IJCAI
1997
15 years 1 months ago
Mini-Buckets: A General Scheme for Generating Approximations in Automated Reasoning
The class of algorithms for approximating reasoning tasks presented in this paper is based on approximating the general bucket elimination framework. The algorithms have adjustabl...
Rina Dechter