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CVPR
2005
IEEE
14 years 10 months ago
Diagram Structure Recognition by Bayesian Conditional Random Fields
Hand-drawn diagrams present a complex recognition problem. Elements of the diagram are often individually ambiguous, and require context to be interpreted. We present a recognitio...
Yuan (Alan) Qi, Martin Szummer, Thomas P. Minka
ICPR
2010
IEEE
14 years 2 months ago
A Meta-Learning Approach to Conditional Random Fields Using Error-Correcting Output Codes
—We present a meta-learning framework for the design of potential functions for Conditional Random Fields. The design of both node potential and edge potential is formulated as a...
Francesco Ciompi, Oriol Pujol, Petia Radeva
IJCNLP
2005
Springer
14 years 2 months ago
Regularisation Techniques for Conditional Random Fields: Parameterised Versus Parameter-Free
Recent work on Conditional Random Fields (CRFs) has demonstrated the need for regularisation when applying these models to real-world NLP data sets. Conventional approaches to regu...
Andrew Smith, Miles Osborne
EMNLP
2009
13 years 6 months ago
Natural Language Generation with Tree Conditional Random Fields
This paper presents an effective method for generating natural language sentences from their underlying meaning representations. The method is built on top of a hybrid tree repres...
Wei Lu, Hwee Tou Ng, Wee Sun Lee
ICML
2006
IEEE
14 years 9 months ago
Accelerated training of conditional random fields with stochastic gradient methods
We apply Stochastic Meta-Descent (SMD), a stochastic gradient optimization method with gain vector adaptation, to the training of Conditional Random Fields (CRFs). On several larg...
S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark ...