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All publications by Alexander T. Ihler
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Decomposition Bounds for Marginal MAP
Wei Ping, Qiang Liu and Alexander T. Ihler
Advances in Neural Information Processing Systems 28, 2015


Probabilistic Variational Bounds for Graphical Models
Qiang Liu, John Iii and Alexander T. Ihler
Advances in Neural Information Processing Systems 28, 2015


Distributed Parameter Estimation via Pseudo-likelihood
Qiang Liu and Alexander T. Ihler
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Bounding the Partition Function using Holder's Inequality
Qiang Liu and Alexander T. Ihler
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Enhanced Gradient and Adaptive Learning Rate for Training Restricted Boltzmann Machines
Kyunghyun Cho, Tapani Raiko and Alexander T. Ihler
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Multicore Gibbs Sampling in Dense, Unstructured Graphs
Tianbing Xu and Alexander T. Ihler
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Learning Scale Free Networks by Reweighted L1 regularization
Qiang Liu and Alexander T. Ihler
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-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


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 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


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


Variational Gaussian-process factor analysis for modeling spatio-temporal data
Jaakko Luttinen and Alexander T. Ihler
Advances in Neural Information Processing Systems 22, 2009


Particle Belief Propagation
Alexander T. Ihler and David A. Mcallester
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09), 2009


Efficient Bayesian Inference for Dynamically Changing Graphs
Ozgur Sumer, Umut Acar, Alexander T. Ihler and Ramgopal R. Mettu
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


Loopy Belief Propagation: Convergence and Effects of Message Errors
Alexander T. Ihler, John Iii and Alan S. Willsky
Journal of Machine Learning Research, 2005


Message Errors in Belief Propagation
Alexander T. Ihler, John W. Fisher and Alan S. Willsky
Advances in Neural Information Processing Systems 17, 2004


Efficient Multiscale Sampling from Products of Gaussian Mixtures
Alexander T. Ihler, Erik B. Sudderth, William T. Freeman and Alan S. Willsky
Advances in Neural Information Processing Systems 16, 2003