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
1832010
Parallel Markov chain Monte Carlo for nonparametric mixture models
S Williamson, A Dubey, E Xing
International Conference on Machine Learning, 98-106, 2013
902013
Variance reduction in stochastic gradient Langevin dynamics
KA Dubey, S J Reddi, SA Williamson, B Poczos, AJ Smola, EP Xing
Advances in neural information processing systems 29, 1154-1162, 2016
682016
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
662013
Dependent Indian buffet processes
S Williamson, P Orbanz, Z Ghahramani
Proceedings of the thirteenth international conference on artificial …, 2010
642010
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
532015
Statistical models for partial membership
KA Heller, S Williamson, Z Ghahramani
Proceedings of the 25th International Conference on Machine learning, 392-399, 2008
532008
Nonparametric network models for link prediction
SA Williamson
The Journal of Machine Learning Research 17 (1), 7102-7121, 2016
492016
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
422013
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
352019
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
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
142020
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
Importance weighted generative networks
M Diesendruck, ER Elenberg, R Sen, GW Cole, S Shakkottai, ...
arXiv preprint arXiv:1806.02512, 2018
122018
Embarrassingly parallel inference for Gaussian processes
MM Zhang, SA Williamson
arXiv preprint arXiv:1702.08420, 2017
112017
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
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Articles 1–20