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− | == Online version ==
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− | [http://www.cs.cornell.edu/~cnyu/papers/icml09_latentssvm.pdf]
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− | == Summary ==
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− | In this [[Category::paper]] author talks about the use of latent variable in the structural SVM.
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− | The paper also identifies the formulation for which their exists effecient algorithm to find the local optimum using convex-concave optimization techniques.
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− | The paper argues that this is the first time latent variable are being used in large margin classifiers.Experiments were then performed in various domains
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− | of computational Biology, IR and NLP to prove the generality of the proposed method.
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− | == Experimentation ==
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− | The experimentations were performbed in many domains and results were as follows
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− | '''Discriminative Motif finding'''
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− | '''Error rate : '''
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− | Gibbs sampler 32.49%
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− | Latent Structural SVM 12%
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− | ''' Noun Phrase Coreference via Clustering '''
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− | '''MITRE Loss:''' SVM cluster 41.3 Latent SVM 35.6
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− | The Structural SVM with latent variable also perform well in the task of Document Retrieval and outperformed List NET and Ranking SVM.
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