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All publications by Padhraic Smyth
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Continuous-Time Regression Models for Longitudinal Networks
Duy Q. Vu, David Hunter, Padhraic Smyth and Arthur U. Asuncion
Advances in Neural Information Processing Systems 24, 2011


Dynamic Egocentric Models for Citation Networks
David Hunter, Padhraic Smyth, Duy Q. Vu and Arthur U. Asuncion
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Revisiting MAP Estimation, Message Passing and Perfect Graphs
James R. Foulds, Nicholas Navaroli, Padhraic Smyth and Alexander T. Ihler
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


A Dynamic Relational Infinite Feature Model for Longitudinal Social Networks
James R. Foulds, Christopher Dubois, Arthur U. Asuncion, Carter T. Butts and Padhraic Smyth
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Particle Filtered MCMC-MLE with Connections to Contrastive Divergence
Arthur U. Asuncion, Qiang Liu, Alexander T. Ihler and Padhraic Smyth
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Learning concept graphs from text with stick-breaking priors
America Chambers, Padhraic Smyth and Mark Steyvers
Advances in Neural Information Processing Systems 23, 2010


Learning with Blocks: Composite Likelihood and Contrastive Divergence
Arthur U. Asuncion, Qiang Liu, Alexander T. Ihler and Padhraic Smyth
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Distributed Algorithms for Topic Models
David Newman, Arthur U. Asuncion, Padhraic Smyth and Max Welling
Journal of Machine Learning Research, 2009


Particle-based Variational Inference for Continuous Systems
Andrew Frank, Padhraic Smyth and Alexander T. Ihler
Advances in Neural Information Processing Systems 22, 2009


Asynchronous Distributed Learning of Topic Models
Padhraic Smyth, Max Welling and Arthur U. Asuncion
Advances in Neural Information Processing Systems 21, 2008


Infinite mixtures of trees
Sergey Kirshner and Padhraic Smyth
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Distributed Inference for Latent Dirichlet Allocation
David Newman, Padhraic Smyth, Max Welling and Arthur U. Asuncion
Advances in Neural Information Processing Systems 20, 2007


Learning Time-Intensity Profiles of Human Activity using Non-Parametric Bayesian Models
Alexander T. Ihler and Padhraic Smyth
Advances in Neural Information Processing Systems 19, 2006


Hierarchical Dirichlet Processes with Random Effects
Seyoung Kim and Padhraic Smyth
Advances in Neural Information Processing Systems 19, 2006


Modeling General and Specific Aspects of Documents with a Probabilistic Topic Model
Chaitanya Chemudugunta, Padhraic Smyth and Mark Steyvers
Advances in Neural Information Processing Systems 19, 2006


Segmental Hidden Markov Models with Random Effects for Waveform Modeling
Seyoung Kim and Padhraic Smyth
Journal of Machine Learning Research, 2006


Joint Probabilistic Curve Clustering and Alignment
Scott J. Gaffney and Padhraic Smyth
Advances in Neural Information Processing Systems 17, 2004


Unsupervised Learning with Permuted Data
Sergey Kirshner, Sridevi Parise and Padhraic Smyth
Proceedings of the 20th International Conference on Machine Learning (ICML-03), 2003


Gene Expression Clustering with Functional Mixture Models
Darya Chudova, Christopher Hart, Eric Mjolsness and Padhraic Smyth
Advances in Neural Information Processing Systems 16, 2003


Learning to Classify Galaxy Shapes Using the EM Algorithm
Sergey Kirshner, Igor V. Cadez, Padhraic Smyth and Chandrika Kamath
Advances in Neural Information Processing Systems 15, 2002