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» Memory-Efficient Inference in Relational Domains
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ECCV
2006
Springer
14 years 6 months ago
Fast Memory-Efficient Generalized Belief Propagation
Generalized Belief Propagation (gbp) has proven to be a promising technique for performing inference on Markov random fields (mrfs). However, its heavy computational cost and large...
M. Pawan Kumar, Philip H. S. Torr
ILP
2007
Springer
13 years 11 months ago
Bias/Variance Analysis for Relational Domains
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
Jennifer Neville, David Jensen
AAAI
2011
12 years 5 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
AAAI
2008
13 years 7 months ago
A General Method for Reducing the Complexity of Relational Inference and its Application to MCMC
Many real-world problems are characterized by complex relational structure, which can be succinctly represented in firstorder logic. However, many relational inference algorithms ...
Hoifung Poon, Pedro Domingos, Marc Sumner