Search Machine Learning Repository: @inproceedings{icml2014c2_tosh14,
    Publisher = {JMLR Workshop and Conference Proceedings},
    Title = {Lower Bounds for the Gibbs Sampler over Mixtures of Gaussians},
    Url = {http://jmlr.org/proceedings/papers/v32/tosh14.pdf},
    Abstract = {The mixing time of a Markov chain is the minimum time $t$ necessary for the total variation distance between the distribution of the Markov chain's current state $X_t$ and its stationary distribution to fall below some $\epsilon > 0$. In this paper, we present lower bounds for the mixing time of the Gibbs sampler over Gaussian mixture models with Dirichlet priors.},
    Author = {Christopher Tosh and Sanjoy Dasgupta},
    Editor = {Tony Jebara and Eric P. Xing},
    Year = {2014},
    Booktitle = {Proceedings of the 31st International Conference on Machine Learning (ICML-14)},
    Pages = {1467-1475}
   }