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ECCV
2006
Springer
15 years 11 months ago
Efficient Belief Propagation with Learned Higher-Order Markov Random Fields
Belief propagation (BP) has become widely used for low-level vision problems and various inference techniques have been proposed for loopy graphs. These methods typically rely on a...
Xiangyang Lan, Stefan Roth, Daniel P. Huttenlocher...
AUSAI
2003
Springer
15 years 2 months ago
Choosing Learning Algorithms Using Sign Tests with High Replicability
An important task in machine learning is determining which learning algorithm works best for a given data set. When the amount of data is small the same data needs to be used repea...
Remco R. Bouckaert
CVPR
2008
IEEE
15 years 11 months ago
Learning Bayesian Networks with qualitative constraints
Graphical models such as Bayesian Networks (BNs) are being increasingly applied to various computer vision problems. One bottleneck in using BN is that learning the BN model param...
Yan Tong, Qiang Ji
WWW
2010
ACM
15 years 4 months ago
A pattern tree-based approach to learning URL normalization rules
Duplicate URLs have brought serious troubles to the whole pipeline of a search engine, from crawling, indexing, to result serving. URL normalization is to transform duplicate URLs...
Tao Lei, Rui Cai, Jiang-Ming Yang, Yan Ke, Xiaodon...
AGENTS
2001
Springer
15 years 2 months ago
Using rat navigation models to learn orientation from visual input on a mobile robot
Rodents possess extraordinary navigation abilities that are far in excess of what current state-of-the-art robot agents are capable of. This paper describes research that is part ...
Brett Browning