Search results
Results: 156
Number of items: 156
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Bornn, L., Chen, Y., de Freitas, N., Eskelin, M., Fang, J., & Welling, M. (2013). Herded Gibbs Sampling. In International Conference on Learning Representation 2013 ArXiv. http://arxiv.org/abs/1301.4168 -
Korattikara, A., Chen, Y., & Welling, M. (2013). Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget. In 2013 JSM proceedings: papers presented at the Joint Statistical Meetings, Montréal, Québec, Canada, August 3-8, 2013, and other ASA-sponsored conferences [cd-rom] (pp. 236-250). American Statistical Association. https://www.amstat.org/meetings/jsm/2013/proceedings.cfm
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Chen, Y., & Welling, M. (2012). Bayesian structure learning for Markov Random Fields with a spike and slab prior. In N. de Freitas, & K. Murphy (Eds.), Uncertainty in Artificial Intelligence: proceedings of the Twenty-Eight conference (2012): August 15-17, 2012, Catalina Island, CA (pp. 174-184). AUAI Press. http://www.auai.org/uai2012/proceedings.pdf
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Gelfand, A. E., & Welling, M. (2012). Generalized belief propagation on tree robust structured region graphs. In K. Murphy, & N. de Freitas (Eds.), Uncertainty in Artificial: proceedings of the Twenty-Eight conference (2012): August 15-17, 2012 Catalina Island, CA (pp. 296-305). AUAI Press. http://www.auai.org/uai2012/proceedings.pdf
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Ahn, S., Korattikara, A., & Welling, M. (2012). Bayesian posterior sampling via stochastic gradient Fisher scoring. In J. Langford, & J. Pineau (Eds.), Proceedings of Twenty-Ninth International Conference Machine Learning. - Vol. 2 (pp. 1591-1598). International Machine Learning Society. http://icml.cc/2012/papers/782.pdf
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Kurihara, K., Welling, M., & Vlassis, N. (2007). Accelerated Variational Dirichlet Process Mixtures. Advances in Neural Information Processing Systems, 19, 761-768. http://www.science.uva.nl/research/isla/pub/Kurihara07nips.pdf
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