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All publications by Chong Wang
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An Adaptive Learning Rate for Stochastic Variational Inference
Rajesh Ranganath, Chong Wang, Blei David and Eric Xing
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Variance Reduction for Stochastic Gradient Optimization
Chong Wang, Xi Chen, Alex Smola and Eric Xing
Advances in Neural Information Processing Systems 26, 2013


Modeling Overlapping Communities with Node Popularities
Prem Gopalan, Chong Wang and David Blei
Advances in Neural Information Processing Systems 26, 2013


Truncation-free Online Variational Inference for Bayesian Nonparametric Models
Chong Wang and David M. Blei
Advances in Neural Information Processing Systems 25, 2012


Latent Collaborative Retrieval
Jason Weston, Chong Wang, Ron Weiss and Adam Berenzweig
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Online Variational Inference for the Hierarchical Dirichlet Process
Chong Wang, John W. Paisley and David M. Blei
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


The Discrete Infinite Logistic Normal Distribution for Mixed-Membership Modeling
John W. Paisley, Chong Wang and David M. Blei
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


The IBP Compound Dirichlet Process and its Application to Focused Topic Modeling
Sinead Williamson, Chong Wang, Katherine A. Heller and David M. Blei
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Fast Large-scale Mixture Modeling with Component-specific Data Partitions
Bo Thiesson and Chong Wang
Advances in Neural Information Processing Systems 23, 2010


Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process
Chong Wang and David M. Blei
Advances in Neural Information Processing Systems 22, 2009


Variational Inference for the Nested Chinese Restaurant Process
Chong Wang and David M. Blei
Advances in Neural Information Processing Systems 22, 2009


Reading Tea Leaves: How Humans Interpret Topic Models
Jonathan Chang, Sean Gerrish, Chong Wang, Jordan L. Boyd-graber and David M. Blei
Advances in Neural Information Processing Systems 22, 2009


Markov Topic Models
Chong Wang, Bo Thiesson, Christopher Meek and David M. Blei
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09), 2009