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ICMLA
2009
13 years 2 months ago
Structured Prediction with Relative Margin
In structured prediction problems, outputs are not confined to binary labels; they are often complex objects such as sequences, trees, or alignments. Support Vector Machine (SVM) ...
Pannagadatta K. Shivaswamy, Tony Jebara
ICML
2005
IEEE
14 years 5 months ago
Learning structured prediction models: a large margin approach
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...
ICML
2005
IEEE
14 years 5 months ago
Learning as search optimization: approximate large margin methods for structured prediction
Mappings to structured output spaces (strings, trees, partitions, etc.) are typically learned using extensions of classification algorithms to simple graphical structures (eg., li...
Daniel Marcu, Hal Daumé III
NAACL
2010
13 years 2 months ago
Softmax-Margin CRFs: Training Log-Linear Models with Cost Functions
We describe a method of incorporating taskspecific cost functions into standard conditional log-likelihood (CLL) training of linear structured prediction models. Recently introduc...
Kevin Gimpel, Noah A. Smith
ICML
2008
IEEE
14 years 5 months ago
Laplace maximum margin Markov networks
We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...
Jun Zhu, Eric P. Xing, Bo Zhang