References
- B. Taskar, C. Guestrin, and D. Koller, "Max Margin Markov Networks," NIPS, vol. 16, 2004.
- I. Tsochantaridis et al., "Support Vector Machine Learning for Interdependent and Structured Output Spaces," Proc. ICML, 2004, pp. 104.
- B. Taskar et al., "Max-Margin Parsing," Proc. EMNLP, 2004.
- C.N. Yu et al., "Support Vector Training of Protein Alignment Models," Proc. RECOMB, 2007, pp. 253-267.
- Y. Yue et al., "A Support Vector Method for Optimization Average Precision," Proc. SIGIR, 2007, pp. 271-278.
- J. Platt, "Sequential Minimal Optimization: A Fast Algorithm for Training Support Vector Machines," Microsoft Research Technical Report MSR-TR-98-14, 1998.
- H. Kim and W. Kim, "Eye Detection in Facial Images Using Zernike Moments with SVM," ETRI J., vol. 30, no. 2, 2008, pp. 335-337. https://doi.org/10.4218/etrij.08.0207.0150
- M. Collins et al., "Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks," JMLR, vol. 9, 2008, pp. 1775-1822.
- N.D. Ratliff, J.A. Bagnell, and M.A. Zinkevich, "(Online) Subgradient Methods for Structured Prediction," Proc. AISTATS, 2007.
- S. Shalev-Shwartz, Y. Singer, and N. Srebro, "Pegasos: Primal Estimated Subgradient Solver for SVM," Proc. ICML, 2007, pp. 807-814.
- C. Lee and M. Jang, "Fast Training of Structured SVM Using Fixed-Threshold Sequential Minimal Optimization," ETRI J., vol. 31, no. 2, 2009, pp. 121-128. https://doi.org/10.4218/etrij.09.0108.0276
- C.H. Teo et al., "A Scalable Modular Convex Solver for Regularized Risk Minimization," Proc. KDD, 2007, pp. 727-736.
- T. Joachims, T. Finley, and C.N. Yu, "Cutting-Plane Training of Structural SVMs," MLJ, vol. 77, no. 1, 2009, pp. 27-59. https://doi.org/10.1258/rsmmlj.77.1.27
- T. Joachims, "Training Linear SVMs in Linear Time," Proc. KDD, 2006, pp. 217-226.
- R. Fan, P. Chen, and C. Lin, "Working Set Selection Using Second Order Information for Training Support Vector Machines," JMLR, vol. 6, 2005, pp. 1889-1918.
- T. Joachims, "A Statistical Learning Model of Text Classification with Support Vector Machines," Proc. SIGIR, 2001, pp. 128-136.
- C. Lin, "Asymptotic Convergence of an SMO Algorithm Without Any Assumptions," IEEE Trans. Neural Networks, vol. 13, no. 1, 2002, pp. 248-250. https://doi.org/10.1109/72.977319
- S. Keerthi and E. Gilbert, "Convergence of a Generalized SMO Algorithm for SVM Classifier Design," Machine Learning, vol. 46, no. 1-3, 2002, pp. 351-360. https://doi.org/10.1023/A:1012431217818
- V. Franc and S. Sonnenburg, "Optimized Cutting Plane Algorithm for Support Vector Machines," Proc. ICML, vol. 307, 2008, pp. 320-327.
- S. Keerthi et al. "A Sequential Dual Method for Large Scale Multi-Class Linear SVMs," Proc. KDD, 2008, pp. 408-416.
- Y. LeCun et al., "Gradient-Based Learning Applied to Document Recognition," Proceedings of the IEEE, vol. 86, no. 11, Nov. 1988, pp. 2278-2324.
- K. Lang. "Newsweeder: Learning to Filter Netnews," Proc. ICML, 1995.
- E.F.T.K. Sang and S. Buchholz. "Introduction to the CoNLL-2000 Shared Task: Chunking," Proc. CoNLL-2000 and LLL-2000, 2000, pp. 127-132.
- D. Lee, H. Rim, and D. Yook, "Automatic Word Spacing Using Probabilistic Models Based on Character n-Grams," IEEE Intelligent Systems, vol. 22, no. 1, 2007, pp. 28-35. https://doi.org/10.1109/MIS.2007.4
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