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» A structural approach to latency prediction
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ICML
2010
IEEE
13 years 11 months ago
Structured Output Learning with Indirect Supervision
We present a novel approach for structure prediction that addresses the difficulty of obtaining labeled structures for training. We observe that structured output problems often h...
Ming-Wei Chang, Vivek Srikumar, Dan Goldwasser, Da...
ISPA
2007
Springer
14 years 4 months ago
Grid and Distributed Public Computing Schemes for Structural Proteomics: A Short Overview
Grid and distributed public computing schemes has become an essential tool for many scientific fields including bioinformatics, computational biology and systems biology. The adopt...
Azhar Ali Shah, Daniel Barthel, Natalio Krasnogor
ICML
2010
IEEE
13 years 11 months ago
Learning Markov Logic Networks Using Structural Motifs
Markov logic networks (MLNs) use firstorder formulas to define features of Markov networks. Current MLN structure learners can only learn short clauses (4-5 literals) due to extre...
Stanley Kok, Pedro Domingos
ACL
2012
12 years 17 days ago
Automatic Event Extraction with Structured Preference Modeling
This paper presents a novel sequence labeling model based on the latent-variable semiMarkov conditional random fields for jointly extracting argument roles of events from texts. ...
Wei Lu, Dan Roth
ICML
2008
IEEE
14 years 11 months ago
Accurate max-margin training for structured output spaces
Tsochantaridis et al. (2005) proposed two formulations for maximum margin training of structured spaces: margin scaling and slack scaling. While margin scaling has been extensivel...
Sunita Sarawagi, Rahul Gupta