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» A New Discriminative Kernel From Probabilistic Models
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EMNLP
2006
13 years 6 months ago
Loss Minimization in Parse Reranking
We propose a general method for reranker construction which targets choosing the candidate with the least expected loss, rather than the most probable candidate. Different approac...
Ivan Titov, James Henderson
JCB
2000
107views more  JCB 2000»
13 years 5 months ago
A Discriminative Framework for Detecting Remote Protein Homologies
A new method for detecting remote protein homologies is introduced and shown to perform well in classifying protein domains by SCOP superfamily. The method is a variant of support...
Tommi Jaakkola, Mark Diekhans, David Haussler
ICCV
2005
IEEE
14 years 7 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
ACL
2012
11 years 7 months ago
Labeling Documents with Timestamps: Learning from their Time Expressions
Temporal reasoners for document understanding typically assume that a document’s creation date is known. Algorithms to ground relative time expressions and order events often re...
Nathanael Chambers
ACL
2007
13 years 6 months ago
A discriminative language model with pseudo-negative samples
In this paper, we propose a novel discriminative language model, which can be applied quite generally. Compared to the well known N-gram language models, discriminative language m...
Daisuke Okanohara, Jun-ichi Tsujii