暂无分享,去创建一个
[1] Honggang Zhang,et al. Variational Bayesian Matrix Factorization for Bounded Support Data , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[2] Jun Guo,et al. Cross-modal subspace learning for sketch-based image retrieval: A comparative study , 2016, 2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC).
[3] Michael I. Jordan,et al. Variational inference for Dirichlet process mixtures , 2006 .
[4] Arne Leijon,et al. Vector quantization of LSF parameters with a mixture of dirichlet distributions , 2013, IEEE Transactions on Audio, Speech, and Language Processing.
[5] Arne Leijon,et al. Human skin color detection in RGB space with Bayesian estimation of beta mixture models , 2010, 2010 18th European Signal Processing Conference.
[6] Chen Shen,et al. A Robust Particle Filtering Algorithm With Non-Gaussian Measurement Noise Using Student-t Distribution , 2014, IEEE Signal Processing Letters.
[7] Jaehoon Jung,et al. Capacity and Error Probability Analysis of Diversity Reception Schemes Over Generalized- $K$ Fading Channels Using a Mixture Gamma Distribution , 2014, IEEE Transactions on Wireless Communications.
[8] Arne Leijon,et al. Human audio-visual consonant recognition analyzed with three bimodal integration models , 2009, INTERSPEECH.
[9] Jun Guo,et al. Dirichlet mixture modeling to estimate an empirical lower bound for LSF quantization , 2014, Signal Process..
[10] Sekino Masashi. Probabilistic Matrix Factorization based on Features , 2010 .
[11] Rainer Martin,et al. Spectral Domain Speech Enhancement Using HMM State-Dependent Super-Gaussian Priors , 2013, IEEE Signal Processing Letters.
[12] Jianhua Zhang,et al. Data scheme-based wireless channel modeling method: motivation, principle and performance , 2017, Journal of Communications and Information Networks.
[13] Zhanyu Ma,et al. A variational Bayes beta Mixture Model for Feature Selection in DNA methylation Studies , 2013, J. Bioinform. Comput. Biol..
[14] Nizar Bouguila,et al. Practical Bayesian estimation of a finite beta mixture through gibbs sampling and its applications , 2006, Stat. Comput..
[15] Jun Guo,et al. Variational Bayesian Learning for Dirichlet Process Mixture of Inverted Dirichlet Distributions in Non-Gaussian Image Feature Modeling , 2019, IEEE Transactions on Neural Networks and Learning Systems.
[16] Arne Leijon,et al. Modelling speech line spectral frequencies with dirichlet mixture models , 2010, INTERSPEECH.
[17] Ruslan Salakhutdinov,et al. Bayesian probabilistic matrix factorization using Markov chain Monte Carlo , 2008, ICML '08.
[18] Zhen Yang,et al. Decorrelation of Neutral Vector Variables: Theory and Applications , 2017, IEEE Transactions on Neural Networks and Learning Systems.
[19] Arne Leijon,et al. Bayesian Estimation of Beta Mixture Models with Variational Inference , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[20] Q. M. Jonathan Wu,et al. A Nonsymmetric Mixture Model for Unsupervised Image Segmentation , 2013, IEEE Transactions on Cybernetics.
[21] Arne Leijon,et al. PDF-optimized LSF vector quantization based on beta mixture models , 2010, INTERSPEECH.
[22] Tommi S. Jaakkola,et al. Tutorial on variational approximation methods , 2000 .
[23] John S. Thompson,et al. Spatial Fading Correlation model using mixtures of Von Mises Fisher distributions , 2009, IEEE Transactions on Wireless Communications.
[24] Perry R. Cook,et al. Bayesian Nonparametric Matrix Factorization for Recorded Music , 2010, ICML.
[25] Jun Guo,et al. Spoofing Detection in Automatic Speaker Verification Systems Using DNN Classifiers and Dynamic Acoustic Features , 2018, IEEE Transactions on Neural Networks and Learning Systems.
[26] Markus Flierl,et al. Probabilistic Multiview Depth Image Enhancement Using Variational Inference , 2015, IEEE Journal of Selected Topics in Signal Processing.
[27] Michael Unser,et al. On the Linearity of Bayesian Interpolators for Non-Gaussian Continuous-Time AR(1) Processes , 2013, IEEE Transactions on Information Theory.
[28] Markus Flierl,et al. Bayesian estimation of Dirichlet mixture model with variational inference , 2014, Pattern Recognit..
[29] Erchin Serpedin,et al. Gaussian Assumption: The Least Favorable but the Most Useful [Lecture Notes] , 2012, IEEE Signal Processing Magazine.
[30] Qie Sun,et al. Statistical analysis of energy consumption patterns on the heat demand of buildings in district heating systems , 2014 .
[31] Keinosuke Fukunaga,et al. Introduction to Statistical Pattern Recognition , 1972 .
[32] Nizar Bouguila,et al. Variational Learning for Finite Dirichlet Mixture Models and Applications , 2012, IEEE Transactions on Neural Networks and Learning Systems.
[33] Zhanyu Ma. Non-Gaussian Statistical Modelsand Their Applications , 2011 .
[34] Jun Guo,et al. Line spectral frequencies modeling by a mixture of von Mises-Fisher distributions , 2015, Signal Process..
[35] Zhanyu Ma. Bayesian estimation of the Dirichlet distribution with expectation propagation , 2012, 2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO).
[36] Jalil Taghia,et al. Variational Inference for Watson Mixture Model , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[37] John D. Lafferty,et al. Correlated Topic Models , 2005, NIPS.
[38] Arne Leijon,et al. Nonnegative HMM for Babble Noise Derived From Speech HMM: Application to Speech Enhancement , 2013, IEEE Transactions on Audio, Speech, and Language Processing.
[39] Zhongwei Si,et al. Learning Deep Features for DNA Methylation Data Analysis , 2016, IEEE Access.
[40] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[41] Jalil Taghia,et al. Bayesian Estimation of the von-Mises Fisher Mixture Model with Variational Inference , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[42] Jun Guo,et al. The Role of Data Analysis in the Development of Intelligent Energy Networks , 2017, IEEE Network.
[43] Jon D. McAuliffe,et al. Variational Inference for Large-Scale Models of Discrete Choice , 2007, 0712.2526.
[44] Michael E. Tipping. Bayesian Inference: An Introduction to Principles and Practice in Machine Learning , 2003, Advanced Lectures on Machine Learning.
[45] Ali Taylan Cemgil,et al. Bayesian inference in hierarchical non‐negative matrix factorisation models of musical sounds , 2008 .
[46] Michael I. Jordan,et al. An Introduction to Variational Methods for Graphical Models , 1999, Machine-mediated learning.
[47] Markus Flierl,et al. Multiview depth map enhancement by variational bayes inference estimation of Dirichlet mixture models , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[48] Arne Leijon,et al. Expectation propagation for estimating the parameters of the beta distribution , 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.
[49] M. Wand,et al. Gaussian Variational Approximate Inference for Generalized Linear Mixed Models , 2012 .
[50] Michael I. Jordan,et al. Probabilistic models of text and images , 2004 .
[51] Zhiguang Xu,et al. Modeling Non-Gaussian Time Series with Nonparametric Bayesian Model , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[52] Jun Guo,et al. Cross-modal subspace learning for fine-grained sketch-based image retrieval , 2017, Neurocomputing.
[53] Stephen P. Boyd,et al. Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.
[54] Yuan Ji,et al. Applications of beta-mixture models in bioinformatics , 2005, Bioinform..
[55] Jun Guo,et al. Feature selection for neutral vector in EEG signal classification , 2016, Neurocomputing.
[56] Stephen M. Stigler,et al. Thomas Bayes's Bayesian Inference , 1982 .
[57] Anil K. Jain,et al. Statistical Pattern Recognition: A Review , 2000, IEEE Trans. Pattern Anal. Mach. Intell..
[58] Arne Leijon,et al. Predictive Distribution of the Dirichlet Mixture Model by Local Variational Inference , 2014, J. Signal Process. Syst..
[59] Zhanyu Ma,et al. A probabilistic principal component analysis based hidden Markov model for audio-visual speech recognition , 2008, 2008 42nd Asilomar Conference on Signals, Systems and Computers.
[60] P. Bickel,et al. Mathematical Statistics: Basic Ideas and Selected Topics , 1977 .
[61] Stephen J. Roberts,et al. A tutorial on variational Bayesian inference , 2012, Artificial Intelligence Review.
[62] Leonardo Zao,et al. Generation of coloured acoustic noise samples with non-Gaussian distributions , 2012, IET Signal Process..
[63] Honggang Zhang,et al. Nonlinear estimation of missing ΔLSF parameters by a mixture of Dirichlet distributions , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).