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» Learning a Generative Model for Structural Representations
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ICCV
2005
IEEE
16 years 4 months ago
Incorporating Visual Knowledge Representation in Stereo Reconstruction
In this paper, we present a two-layer generative model that incorporates generic middle-level visual knowledge for dense stereo reconstruction. The visual knowledge is represented...
Adrian Barbu, Song Chun Zhu
UAI
2003
15 years 3 months ago
Large-Sample Learning of Bayesian Networks is NP-Hard
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...
David Maxwell Chickering, Christopher Meek, David ...
JMLR
2006
118views more  JMLR 2006»
15 years 2 months ago
Learning Factor Graphs in Polynomial Time and Sample Complexity
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
Pieter Abbeel, Daphne Koller, Andrew Y. Ng
118
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CODES
2006
IEEE
15 years 8 months ago
Generic netlist representation for system and PE level design exploration
Designer productivity and design predictability are vital factors for successful embedded system design. Shrinking time-to-market and increasing complexity of these systems requir...
Bita Gorjiara, Mehrdad Reshadi, Pramod Chandraiah,...
RECOMB
2003
Springer
16 years 2 months ago
Modeling dependencies in protein-DNA binding sites
The availability of whole genome sequences and high-throughput genomic assays opens the door for in silico analysis of transcription regulation. This includes methods for discover...
Yoseph Barash, Gal Elidan, Nir Friedman, Tommy Kap...