Max-Margin Infinite Hidden Markov Models
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Bo Zhang | Jun Zhu | Aonan Zhang | Jun Zhu | Bo Zhang | Aonan Zhang
[1] Babak Shahbaba,et al. Nonlinear Models Using Dirichlet Process Mixtures , 2007, J. Mach. Learn. Res..
[2] Ning Chen,et al. Gibbs max-margin topic models with data augmentation , 2013, J. Mach. Learn. Res..
[3] Chris H. Q. Ding,et al. Multi-class protein fold recognition using support vector machines and neural networks , 2001, Bioinform..
[4] Sotirios Chatzis,et al. Infinite Markov-Switching Maximum Entropy Discrimination Machines , 2013, ICML.
[5] Jonathan P. How,et al. Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture , 2013, NIPS.
[6] Michael I. Jordan,et al. Hierarchical Dirichlet Processes , 2006 .
[7] J. Pitman. Combinatorial Stochastic Processes , 2006 .
[8] Warren B. Powell,et al. Dirichlet Process Mixtures of Generalized Linear Models , 2009, J. Mach. Learn. Res..
[9] L. Devroye. Non-Uniform Random Variate Generation , 1986 .
[10] Lawrence K. Saul,et al. Large Margin Hidden Markov Models for Automatic Speech Recognition , 2006, NIPS.
[11] Bingbing Ni,et al. RGBD-HuDaAct: A color-depth video database for human daily activity recognition , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).
[12] François Laviolette,et al. PAC-Bayesian learning of linear classifiers , 2009, ICML '09.
[13] Koby Crammer,et al. On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines , 2002, J. Mach. Learn. Res..
[14] W. R. Schucany,et al. Generating Random Variates Using Transformations with Multiple Roots , 1976 .
[15] Ning Chen,et al. Infinite SVM: a Dirichlet Process Mixture of Large-margin Kernel Machines , 2011, ICML.
[16] C. Antoniak. Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric Problems , 1974 .
[17] J. Pitman. Exchangeable and partially exchangeable random partitions , 1995 .
[18] Yee Whye Teh,et al. Beam sampling for the infinite hidden Markov model , 2008, ICML '08.
[19] Thomas Hofmann,et al. Hidden Markov Support Vector Machines , 2003, ICML.
[20] Nicholas G. Polson,et al. Data augmentation for support vector machines , 2011 .
[21] Thomas L. Griffiths,et al. The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies , 2007, JACM.
[22] Jun Zhou,et al. Mixing Linear SVMs for Nonlinear Classification , 2010, IEEE Transactions on Neural Networks.
[23] Yihong Gong,et al. Locality-constrained Linear Coding for image classification , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[24] Samy Bengio,et al. A Parallel Mixture of SVMs for Very Large Scale Problems , 2001, Neural Computation.
[25] John Shawe-Taylor,et al. PAC-Bayes & Margins , 2002, NIPS.
[26] Lawrence R. Rabiner,et al. A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.
[27] Carl E. Rasmussen,et al. Factorial Hidden Markov Models , 1997 .
[28] Ning Chen,et al. Gibbs Max-Margin Topic Models with Fast Sampling Algorithms , 2013, ICML.
[29] Tommi S. Jaakkola,et al. Maximum Entropy Discrimination , 1999, NIPS.
[30] T. Ferguson. A Bayesian Analysis of Some Nonparametric Problems , 1973 .
[31] Ben Taskar,et al. Max-Margin Markov Networks , 2003, NIPS.
[32] S. L. Scott. Bayesian Methods for Hidden Markov Models , 2002 .