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IJCNLP
2005
Springer
13 years 10 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
INLG
2010
Springer
13 years 2 months ago
Poly-co: An Unsupervised Co-reference Detection System
We describe our contribution to the Generation Challenge 2010 for the tasks of Named Entity Recognition and coreference detection (GREC-NER). To extract the NE and the referring e...
Eric Charton, Michel Gagnon, Benoît Ozell
CVPR
2003
IEEE
14 years 6 months ago
Man-Made Structure Detection in Natural Images using a Causal Multiscale Random Field
This paper presents a generative model based approach to man-made structure detection in 2D natural images. The proposed approach uses a causal multiscale random field suggested i...
Sanjiv Kumar, Martial Hebert
ACL
2006
13 years 6 months ago
Combining Statistical and Knowledge-Based Spoken Language Understanding in Conditional Models
Spoken Language Understanding (SLU) addresses the problem of extracting semantic meaning conveyed in an utterance. The traditional knowledge-based approach to this problem is very...
Ye-Yi Wang, Alex Acero, Milind Mahajan, John Lee
EMNLP
2006
13 years 6 months ago
A Hybrid Markov/Semi-Markov Conditional Random Field for Sequence Segmentation
Markov order-1 conditional random fields (CRFs) and semi-Markov CRFs are two popular models for sequence segmentation and labeling. Both models have advantages in terms of the typ...
Galen Andrew