References:

D.M. Blei, A.Y. Ng, M.I. Jordan Latent dirichlet allocation Journal of machine Learning research, 3 (Jan) (2003), pp. 993-1022

L. Fei-Fei, P. Perona A bayesian hierarchical model for learning natural scene categories Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, 2, IEEE (2005), pp. 524-531

K.L. Caballero, J. Barajas, R. Akella The generalized dirichlet distribution in enhanced topic detection Proceedings of the 21st ACM international conference on Information and knowledge management, ACM(2012), pp. 773-782

D.M. Blei Probabilistic models of text and images, University of California, Berkeley (2004)

D. Blei, J. Lafferty Correlated topic models Advances in neural information processing systems, 18 (2006), p. 147

W. Li, D. Blei, A. McCallum Nonparametric bayes pachinko allocation Proceedings of the Twenty-Third Conference on Uncertainty in Artificial Intelligence, AUAI Press (2007), pp. 243-250

W. Li, A. McCallum Pachinko allocation: Dag-structured mixture models of topic correlations Proceedings of the 23rd international conference on Machine learning, ACM (2006), pp. 577-584

D.P. Putthividhya, H.T. Attias, S. Nagarajan Independent factor topic models Proceedings of the 26th Annual International Conference on Machine Learning, ACM (2009), pp. 833-840

D.P. Putthividhya A family of statistical topic models for text and multimedia documents, University of California at San Diego (2010)

A.S. Bakhtiari, N. Bouguila A variational bayes model for count data learning and classification Engineering Applications of Artificial Intelligence, 35 (2014), pp. 176-186

R.J. Connor, J.E. Mosimann Concepts of independence for proportions with a generalization of the dirichlet distribution Journal of the American Statistical Association, 64 (325) (1969), pp. 194-206

Y. Rui, T. Huang Optimizing learning in image retrieval Computer Vision and Pattern Recognition, 2000. Proceedings. IEEE Conference on, 1, IEEE (2000), pp. 236-243

C.B. Akgul, B. Sankur, Y. Yemez, F. Schmitt Similarity learning for 3d object retrieval using relevance feedback and risk minimization International Journal of Computer Vision, 89 (2-3) (2010), pp. 392-407

B. Hu, Y. Liu, S. Gao, R. Sun, C. Xian Parallel relevance feedback for 3d model retrieval based on fast weighted-center particle swarm optimization Pattern Recognition, 43 (8) (2010), pp. 2950-2961

D. Giorgi, M. Mortara, M. Spagnuolo 3d shape retrieval based on best view selection Proceedings of the ACM workshop on 3D object retrieval, ACM (2010), pp. 9-14

G. Leifman, R. Meir, A. Tal Semantic-oriented 3d shape retrieval using relevance feedback The Visual Computer, 21 (8-10) (2005), pp. 865-875

Y.W. Teh, D. Newman, M. Welling A collapsed variational bayesian inference algorithm for latent dirichlet allocation Advances in neural information processing systems (2007), pp. 1353-1360

S. Deerwester, S.T. Dumais, G.W. Furnas, T.K. Landauer, R. Harshman Indexing by latent semantic analysis Journal of the American society for information science, 41 (6) (1990), p. 391

C.H. Papadimitriou, H. Tamaki, P. Raghavan, S. Vempala Latent semantic indexing: A probabilistic analysis Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems, ACM (1998), pp. 159-168

T. Hofmann Probabilistic latent semantic indexing Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval, ACM (1999), pp. 50-57

N. Bouguila, D. Ziou A dirichlet process mixture of generalized dirichlet distributions for proportional data modeling IEEE Transactions on Neural Networks, 21 (1) (2010), pp. 107-122

A.S. Bakhtiari, N. Bouguila A latent beta-liouville allocation model Expert Systems with Applications, 45 (2016), pp. 260-272

Y.W. Teh, D. Newman, M. Welling A collapsed variational bayesian inference algorithm for latent dirichlet allocation Advances in neural information processing systems (2007), pp. 1353-1360

N. Bouguila Clustering of count data using generalized dirichlet multinomial distributions IEEE Transactions on Knowledge and Data Engineering, 20 (4) (2008), pp. 462-474

A.C. Damianou, M.K. Titsias, N.D. Lawrence Variational inference for latent variables and uncertain inputs in gaussian processes Journal of Machine Learning Research (JMLR), 2 (2015)

R. Nallapati Discriminative models for information retrieval Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval, ACM (2004), pp. 64-71

D.M. Blei, M.I. Jordan, et al. Variational inference for dirichlet process mixtures Bayesian analysis, 1 (1) (2006), pp. 121-144

I. Sato, H. Nakagawa Rethinking collapsed variational bayes inference for lda Proceedings of the 29th International Coference on International Conference on Machine Learning, Omnipress (2012), pp. 763-770

J. Foulds, L. Boyles, C. DuBois, P. Smyth, M. Welling Stochastic collapsed variational bayesian inference for latent dirichlet allocation Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, ACM (2013), pp. 446-454

B. Leng, J. Zeng, M. Yao, Z. Xiong 3d object retrieval with multitopic model combining relevance feedback and lda model IEEE Transactions on Image Processing, 24 (1) (2015), pp. 94-105

A. Asuncion, M. Welling, P. Smyth, Y.W. Teh On smoothing and inference for topic models Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, AUAI Press (2009), pp. 27-34

H.M. Wallach, I. Murray, R. Salakhutdinov, D. Mimno Evaluation methods for topic models Proceedings of the 26th annual international conference on machine learning, ACM (2009), pp. 1105-1112

S. Lazebnik, C. Schmid, J. Ponce Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’06), 2(2006), pp. 2169-2178

W. Fan, N. Bouguila Face detection and facial expression recognition using a novel variational statistical framework International Conference on Multimedia Communications, Services and Security, Springer (2012), pp. 95-106

W. Fan, N. Bouguila Learning finite beta-liouville mixture models via variational bayes for proportional data clustering. IJCAI (2013), pp. 1323-1329

G. Zhao, M. Pietikainen Dynamic texture recognition using local binary patterns with an application to facial expressions IEEE transactions on pattern analysis and machine intelligence, 29 (6) (2007), pp. 915-928

S. Savarese, L. Fei-Fei 3d generic object categorization, localization and pose estimation Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on, IEEE (2007), pp. 1-8

S. Vishwakarma, A. Agrawal A survey on activity recognition and behavior understanding in video surveillance The Visual Computer, 29 (10) (2013), pp. 983-1009

I. Laptev, T. Lindeberg Velocity adaptation of space-time interest points Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on, 1, IEEE(2004), pp. 52-56

C. Schuldt, I. Laptev, B. Caputo Recognizing human actions: a local svm approach Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on, 3, IEEE(2004), pp. 32-36

B.K. Horn, B.G. Schunck Determining optical flow Artificial intelligence, 17 (1-3) (1981), pp. 185-203

N. Bouguila, D. Ziou, R.I. Hammoud On bayesian analysis of a finite generalized dirichlet mixture via a metropolis-within-gibbs sampling Pattern Anal. Appl., 12 (2) (2009), pp. 151-166

N. Bouguila Count data modeling and classification using finite mixtures of distributions IEEE Trans. Neural Networks, 22 (2) (2011), pp. 186-198