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ICML
2010
IEEE
15 years 7 months ago
Bottom-Up Learning of Markov Network Structure
The structure of a Markov network is typically learned using top-down search. At each step, the search specializes a feature by conjoining it to the variable or feature that most ...
Jesse Davis, Pedro Domingos
CORR
2012
Springer
185views Education» more  CORR 2012»
14 years 2 months ago
Bayesian network learning with cutting planes
The problem of learning the structure of Bayesian networks from complete discrete data with a limit on parent set size is considered. Learning is cast explicitly as an optimisatio...
James Cussens
ICIP
2005
IEEE
16 years 8 months ago
Layered local prediction network with dynamic learning for face super-resolution
In this paper, we propose a novel framework for face super-resolution based on a layered predictor network. In the first layer, multiple predictors are trained online with a dynami...
Dahua Lin, Wei Liu, Xiaoou Tang
ICDE
2007
IEEE
115views Database» more  ICDE 2007»
16 years 8 months ago
SPRITE: A Learning-Based Text Retrieval System in DHT Networks
In this paper, we propose SPRITE (Selective PRogressive Index Tuning by Examples), a scalable system for text retrieval in a structured P2P network. Under SPRITE, each peer is res...
Yingguang Li, H. V. Jagadish, Kian-Lee Tan
CVPR
2010
IEEE
16 years 2 months ago
Learning from Interpolated Images using Neural Networks for Digital Forensics
Interpolated images have data redundancy, and special correlation exists among neighboring pixels, which is a crucial clue in digital forensics. We design a neural network based f...
Yizhen Huang, Na Fan