Sinead Williamson
Sinead Williamson
Assistant professor, University of Texas at Austin
Verified email at
TitleCited byYear
The IBP compound Dirichlet process and its application to focused topic modeling
S Williamson, C Wang, KA Heller, DM Blei
Proceedings of the 27th international conference on machine learning (ICML …, 2010
Parallel Markov chain Monte Carlo for nonparametric mixture models
S Williamson, A Dubey, E Xing
International Conference on Machine Learning, 98-106, 2013
A nonparametric mixture model for topic modeling over time
A Dubey, A Hefny, S Williamson, EP Xing
Proceedings of the 2013 SIAM International Conference on Data Mining, 530-538, 2013
Dependent Indian buffet processes
S Williamson, P Orbanz, Z Ghahramani
Proceedings of the thirteenth international conference on artificial …, 2010
Statistical models for partial membership
KA Heller, S Williamson, Z Ghahramani
Proceedings of the 25th international conference on Machine learning, 392-399, 2008
Estimating network degree distributions under sampling: An inverse problem, with applications to monitoring social media networks
Y Zhang, ED Kolaczyk, BD Spencer
The Annals of Applied Statistics 9 (1), 166-199, 2015
A survey of non-exchangeable priors for Bayesian nonparametric models
NJ Foti, SA Williamson
IEEE transactions on pattern analysis and machine intelligence 37 (2), 359-371, 2013
Variance reduction in stochastic gradient Langevin dynamics
KA Dubey, SJ Reddi, SA Williamson, B Poczos, AJ Smola, EP Xing
Advances in neural information processing systems, 1154-1162, 2016
Nonparametric network models for link prediction
SA Williamson
The Journal of Machine Learning Research 17 (1), 7102-7121, 2016
Focused topic models
S Williamson, C Wang, K Heller, D Blei
NIPS Workshop on Applications for Topic Models: Text and Beyond, 1-4, 2009
Modeling images using transformed indian buffet processes
K Zhai, Y Hu, S Williamson, J Boyd-Graber
arXiv preprint arXiv:1206.6482, 2012
A unifying representation for a class of dependent random measures
N Foti, J Futoma, D Rockmore, S Williamson
Artificial Intelligence and Statistics, 20-28, 2013
Probabilistic models for data combination in recommender systems
S Williamson, Z Ghahramani
NIPS 2008 Workshop: Learning from Multiple Sources, 2008
Parallel markov chain monte carlo for pitman-yor mixture models
A Dubey, S Williamson, E P Xing
figshare, 2014
Restricting exchangeable nonparametric distributions
SA Williamson, SN MacEachern, EP Xing
Advances in Neural Information Processing Systems, 2598-2606, 2013
Dependent nonparametric trees for dynamic hierarchical clustering
KA Dubey, Q Ho, SA Williamson, EP Xing
Advances in Neural Information Processing Systems, 1152-1160, 2014
Slice sampling normalized kernel-weighted completely random measure mixture models
N Foti, S Williamson
Advances in Neural Information Processing Systems, 2240-2248, 2012
Unit–rate Poisson representations of completely random measures
P Orbanz, S Williamson
Electronic Journal of Statistics, 1-12, 2011
Restricted Indian buffet processes
F Doshi-Velez, SA Williamson
Statistics and Computing 27 (5), 1205-1223, 2017
Scalable Bayesian Nonparametric Clustering and Classification
Y Ni, P Müller, M Diesendruck, S Williamson, Y Zhu, Y Ji
Journal of Computational and Graphical Statistics, 1-45, 2019
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Articles 1–20