Laplace maximum margin Markov networks
暂无分享,去创建一个
[1] Tommi S. Jaakkola,et al. Maximum Entropy Discrimination , 1999, NIPS.
[2] John D. Lafferty,et al. Boosting and Maximum Likelihood for Exponential Models , 2001, NIPS.
[3] Thomas Hofmann,et al. Hidden Markov Support Vector Machines , 2003, ICML.
[4] Ben Taskar,et al. Max-Margin Markov Networks , 2003, NIPS.
[5] Xavier Carreras,et al. Exponentiated gradient algorithms for log-linear structured prediction , 2007, ICML '07.
[6] Nathan Ratliff,et al. Online) Subgradient Methods for Structured Prediction , 2007 .
[7] Martin J. Wainwright,et al. High-Dimensional Graphical Model Selection Using ℓ1-Regularized Logistic Regression , 2006, NIPS.
[8] B. Schölkopf,et al. High-Dimensional Graphical Model Selection Using ℓ1-Regularized Logistic Regression , 2007 .
[9] Ben Taskar,et al. Exponentiated Gradient Algorithms for Large-margin Structured Classification , 2004, NIPS.
[10] Andrew McCallum,et al. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.
[11] Mário A. T. Figueiredo. Adaptive Sparseness for Supervised Learning , 2003, IEEE Trans. Pattern Anal. Mach. Intell..
[12] Alexander J. Smola,et al. Support vector machine learning , 2001, Tutorial Guide. ISCAS 2001. IEEE International Symposium on Circuits and Systems (Cat. No.01TH8573).
[13] Jianfeng Gao,et al. Scalable training of L1-regularized log-linear models , 2007, ICML '07.
[14] John Langford,et al. An Improved Predictive Accuracy Bound for Averaging Classifiers , 2001, ICML.
[15] O. Mangasarian,et al. Robust linear programming discrimination of two linearly inseparable sets , 1992 .
[16] Miroslav Dudík,et al. Maximum Entropy Density Estimation with Generalized Regularization and an Application to Species Distribution Modeling , 2007, J. Mach. Learn. Res..
[17] Nuno Vasconcelos,et al. Direct convex relaxations of sparse SVM , 2007, ICML '07.
[18] Yuan Qi,et al. Bayesian Conditional Random Fields , 2005, AISTATS.
[19] Daphne Koller,et al. Efficient Structure Learning of Markov Networks using L1-Regularization , 2006, NIPS.
[20] Thomas Hofmann,et al. Support vector machine learning for interdependent and structured output spaces , 2004, ICML.
[21] Ben Taskar,et al. Structured Prediction via the Extragradient Method , 2005, NIPS.
[22] Ata Kabán,et al. On Bayesian classification with Laplace priors , 2007, Pattern Recognit. Lett..
[23] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .