Sinead Williamson
Sinead Williamson
Assistant professor, University of Texas at Austin
Verified email at mccombs.utexas.edu
Title
Cited by
Cited by
Year
The IBP compound Dirichlet process and its application to focused topic modeling
S Williamson, C Wang, KA Heller, DM Blei
ICML, 2010
1682010
Parallel Markov chain Monte Carlo for nonparametric mixture models
S Williamson, A Dubey, E Xing
International Conference on Machine Learning, 98-106, 2013
802013
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
632013
Dependent Indian buffet processes
S Williamson, P Orbanz, Z Ghahramani
Proceedings of the thirteenth international conference on artificial …, 2010
552010
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
482016
Statistical models for partial membership
KA Heller, S Williamson, Z Ghahramani
Proceedings of the 25th international conference on Machine learning, 392-399, 2008
482008
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
452015
Nonparametric network models for link prediction
SA Williamson
The Journal of Machine Learning Research 17 (1), 7102-7121, 2016
382016
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
382013
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
192013
Focused topic models
S Williamson, C Wang, K Heller, D Blei
NIPS Workshop on Applications for Topic Models: Text and Beyond, 1-4, 2009
182009
The influence of 15-week exercise training on dietary patterns among young adults
J Joo, SA Williamson, AI Vazquez, JR Fernandez, MS Bray
International Journal of Obesity 43 (9), 1681-1690, 2019
142019
Probabilistic models for data combination in recommender systems
S Williamson, Z Ghahramani
NIPS 2008 Workshop: Learning from Multiple Sources, 2008
132008
Parallel markov chain monte carlo for pitman-yor mixture models
A Dubey, S Williamson, E P Xing
Carnegie Mellon University, 2014
112014
Modeling images using transformed Indian buffet processes
Y Hu, K Zhai, S Williamson, J Boyd-Graber
International Conference of Machine Learning 8, 2012
112012
Unit–rate Poisson representations of completely random measures
P Orbanz, S Williamson
Electronic Journal of Statistics 5, 1354-1373, 2011
112011
Restricting exchangeable nonparametric distributions
SA Williamson, SN MacEachern, EP Xing
Advances in Neural Information Processing Systems, 2598-2606, 2013
102013
Dependent nonparametric trees for dynamic hierarchical clustering
KA Dubey, Q Ho, SA Williamson, EP Xing
Advances in Neural Information Processing Systems, 1152-1160, 2014
92014
Slice sampling normalized kernel-weighted completely random measure mixture models
N Foti, S Williamson
Advances in Neural Information Processing Systems, 2240-2248, 2012
82012
Restricted Indian buffet processes
F Doshi-Velez, SA Williamson
Statistics and Computing 27 (5), 1205-1223, 2017
72017
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Articles 1–20