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
1792010
Parallel Markov chain Monte Carlo for nonparametric mixture models
S Williamson, A Dubey, E Xing
International Conference on Machine Learning, 98-106, 2013
862013
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
672013
Dependent Indian buffet processes
S Williamson, P Orbanz, Z Ghahramani
Proceedings of the thirteenth international conference on artificial …, 2010
632010
Variance reduction in stochastic gradient Langevin dynamics
A Dubey, SJ Reddi, B Póczos, AJ Smola, EP Xing, SA Williamson
Advances in neural information processing systems 29, 1154, 2016
612016
Estimating network degree distributions under sampling: An inverse problem, with applications to monitoring social media networks
Y Zhang, ED Kolaczyk, BD Spencer
Annals of Applied Statistics 9 (1), 166-199, 2015
522015
Statistical models for partial membership
KA Heller, S Williamson, Z Ghahramani
Proceedings of the 25th International Conference on Machine learning, 392-399, 2008
522008
Nonparametric network models for link prediction
SA Williamson
The Journal of Machine Learning Research 17 (1), 7102-7121, 2016
482016
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
412013
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
302019
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
202013
Focused topic models
S Williamson, C Wang, K Heller, D Blei
NIPS Workshop on Applications for Topic Models: Text and Beyond, 1-4, 2009
202009
Parallel markov chain monte carlo for pitman-yor mixture models
A Dubey, S Williamson, E P Xing
Carnegie Mellon University, 2014
132014
Modeling images using transformed Indian buffet processes
Y Hu, K Zhai, S Williamson, J Boyd-Graber
International Conference of Machine Learning 8, 2012
132012
Probabilistic models for data combination in recommender systems
S Williamson, Z Ghahramani
NIPS 2008 Workshop: Learning from Multiple Sources, 2008
132008
Scalable Bayesian nonparametric clustering and classification
Y Ni, P Müller, M Diesendruck, S Williamson, Y Zhu, Y Ji
Journal of Computational and Graphical Statistics 29 (1), 53-65, 2020
122020
Importance weighted generative networks
M Diesendruck, ER Elenberg, R Sen, GW Cole, S Shakkottai, ...
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2019
122019
Dependent nonparametric trees for dynamic hierarchical clustering
K Dubey, Q Ho, S Williamson, E P Xing
Carnegie Mellon University, 2014
112014
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
S Williamson, Z Ghahramani, SN MacEachern, EP Xing
arXiv preprint arXiv:1209.1145, 2012
102012
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