Discriminative Learning for Dynamic State Prediction
暂无分享,去创建一个
[1] Andrew McCallum,et al. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.
[2] Trevor Darrell,et al. Conditional Random People: Tracking Humans with CRFs and Grid Filters , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[3] Yaakov Bar-Shalom,et al. Estimation and Tracking: Principles, Techniques, and Software , 1993 .
[4] Franz Pernkopf,et al. Discriminative versus generative parameter and structure learning of Bayesian network classifiers , 2005, ICML.
[5] Cristian Sminchisescu,et al. Discriminative density propagation for 3D human motion estimation , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[6] Bin Shen,et al. Structural Extension to Logistic Regression: Discriminative Parameter Learning of Belief Net Classifiers , 2002, Machine Learning.
[7] A. Ran,et al. Necessary and sufficient conditions for the existence of a positive definite solution of the matrix equation X + A*X-1A = Q , 1993 .
[8] Fernando Pereira,et al. Shallow Parsing with Conditional Random Fields , 2003, NAACL.
[9] Robert A. Jacobs,et al. Hierarchical Mixtures of Experts and the EM Algorithm , 1993, Neural Computation.
[10] Vladimir Pavlovic,et al. Discriminative Learning of Mixture of Bayesian Network Classifiers for Sequence Classification , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[11] Andrew McCallum,et al. Maximum Entropy Markov Models for Information Extraction and Segmentation , 2000, ICML.
[12] Zoubin Ghahramani,et al. Learning Nonlinear Dynamical Systems Using an EM Algorithm , 1998, NIPS.
[13] Sebastian Thrun,et al. Discriminative Training of Kalman Filters , 2005, Robotics: Science and Systems.
[14] Edward H. Adelson,et al. Learning Gaussian Conditional Random Fields for Low-Level Vision , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[15] David J. C. MacKay,et al. A Practical Bayesian Framework for Backpropagation Networks , 1992, Neural Computation.
[16] Daniel Povey,et al. Large scale discriminative training of hidden Markov models for speech recognition , 2002, Comput. Speech Lang..
[17] Michael I. Jordan,et al. Distance Metric Learning with Application to Clustering with Side-Information , 2002, NIPS.
[18] David J. Fleet,et al. Priors for people tracking from small training sets , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[19] Yee Whye Teh,et al. An Alternate Objective Function for Markovian Fields , 2002, ICML.
[20] Xiaojin Zhu,et al. Kernel conditional random fields: representation and clique selection , 2004, ICML.
[21] Douglas A. Wolfe,et al. Nonparametric Statistical Methods , 1973 .
[22] Richard S. Zemel,et al. Combining discriminative features to infer complex trajectories , 2006, ICML.
[23] David J. Fleet,et al. Robust Online Appearance Models for Visual Tracking , 2003, IEEE Trans. Pattern Anal. Mach. Intell..
[24] Vladimir Pavlovic,et al. Efficient discriminative learning of Bayesian network classifier via boosted augmented naive Bayes , 2005, ICML '05.
[25] Rui Li,et al. Articulated Pose Estimation in a Learned Smooth Space of Feasible Solutions , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.
[26] Neil D. Lawrence,et al. Gaussian Process Latent Variable Models for Human Pose Estimation , 2007, MLMI.
[27] Rudolph van der Merwe,et al. The square-root unscented Kalman filter for state and parameter-estimation , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).
[28] J. Engwerda. On the existence of a positive definite solution of the matrix equation X + A , 1993 .
[29] Michael I. Jordan. Graphical Models , 1998 .
[30] David J. Fleet,et al. 3D People Tracking with Gaussian Process Dynamical Models , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[31] Michael I. Jordan,et al. On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes , 2001, NIPS.