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NIPS
2004
13 years 8 months ago
Semi-Markov Conditional Random Fields for Information Extraction
We describe semi-Markov conditional random fields (semi-CRFs), a conditionally trained version of semi-Markov chains. Intuitively, a semiCRF on an input sequence x outputs a "...
Sunita Sarawagi, William W. Cohen
ACL
2009
13 years 5 months ago
Stochastic Gradient Descent Training for L1-regularized Log-linear Models with Cumulative Penalty
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
Yoshimasa Tsuruoka, Jun-ichi Tsujii, Sophia Anania...
ICCPOL
2009
Springer
13 years 5 months ago
A Simple and Efficient Model Pruning Method for Conditional Random Fields
Conditional random fields (CRFs) have been quite successful in various machine learning tasks. However, as larger and larger data become acceptable for the current computational ma...
Hai Zhao, Chunyu Kit
CANDC
2004
ACM
13 years 7 months ago
iProLINK: an integrated protein resource for literature mining
The exponential growth of large-scale molecular sequence data and of the PubMed scientific literature has prompted active research in biological literature mining and information ...
Zhang-Zhi Hu, Inderjeet Mani, Vincent Hermoso, Hon...
ICDM
2002
IEEE
138views Data Mining» more  ICDM 2002»
14 years 12 days ago
Extraction Techniques for Mining Services from Web Sources
The Web has established itself as the dominant medium for doing electronic commerce. Consequently the number of service providers, both large and small, advertising their services...
Hasan Davulcu, Saikat Mukherjee, I. V. Ramakrishna...