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» Approximate algorithms for neural-Bayesian approaches
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AGI
2008
14 years 11 months ago
A computational approximation to the AIXI model
Universal induction solves in principle the problem of choosing a prior to achieve optimal inductive inference. The AIXI theory, which combines control theory and universal induct...
Sergey Pankov
COR
2007
108views more  COR 2007»
14 years 9 months ago
New primal-dual algorithms for Steiner tree problems
We present new primal-dual algorithms for several network design problems. The problems considered are the generalized Steiner tree problem (GST), the directed Steiner tree proble...
Vardges Melkonian
CP
2008
Springer
14 years 11 months ago
Approximate Solution Sampling (and Counting) on AND/OR Spaces
In this paper, we describe a new algorithm for sampling solutions from a uniform distribution over the solutions of a constraint network. Our new algorithm improves upon the Sampli...
Vibhav Gogate, Rina Dechter
ICDE
1996
IEEE
142views Database» more  ICDE 1996»
15 years 11 months ago
Approximate Queries and Representations for Large Data Sequences
Many new database application domains such as experimental sciences and medicine are characterized by large sequences as their main form of data. Using approximate representation ...
Hagit Shatkay, Stanley B. Zdonik
CVPR
2005
IEEE
15 years 11 months ago
Rank-R Approximation of Tensors: Using Image-as-Matrix Representation
We present a novel multilinear algebra based approach for reduced dimensionality representation of image ensembles. We treat an image as a matrix, instead of a vector as in tradit...
Hongcheng Wang, Narendra Ahuja