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Results: 160
Number of items: 160
  • Open Access
    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
  • Open Access
    Welinder, P., Welling, M., & Perona, P. (2013). A Lazy Man's Approach to Benchmarking: Semisupervised Classifier Evaluation and Recalibration. In Proceedings: 2013 IEEE Conference on Computer Vision and Pattern Recognition: CVPR 2013 : 23-28 June 2013, Portland, Oregon, USA (pp. 3262-3269). IEEE Computer Society, Conference Publishing Services. https://doi.org/10.1109/CVPR.2013.419
  • Open Access
    Chen, Y., & Welling, M. (2013). Evidence Estimation for Bayesian Partially Observed MRFs. JMLR Workshop and Conference Proceedings, 31, 178-186. http://jmlr.org/proceedings/papers/v31/chen13c.html
  • Open Access
    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
  • Open Access
    Boyles, L., & Welling, M. (2013). The time-marginalized coalescent prior for hierarchical clustering. In P. Bartlett, F. C. N. Pereira, C. J. C. Burges, L. Bottou, & K. Q. Weinberger (Eds.), 26th Annual Conference on Neural Information Processing Systems 2012: December 3-6, 2012, Lake Tahoe, Nevada, USA (Vol. 4, pp. 2969-2977). (Advances in Neural Information Processing Systems; Vol. 25). Curran Associates. https://papers.nips.cc/paper/4786-the-time-marginalized-coalescent-prior-for-hierarchical-clustering
  • Open Access
    Ahn, S., Chen, Y., & Welling, M. (2013). Distributed and Adaptive Darting Monte Carlo through Regenerations. JMLR Workshop and Conference Proceedings, 31, 108-116. http://jmlr.org/proceedings/papers/v31/ahn13a.html
  • Open Access
    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
  • Open Access
    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
  • Open Access
    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
  • 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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