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All publications by Andrew Mccallum
authors venues years



MAP Inference in Chains using Column Generation
David Belanger, Alexandre Passos, Sebastian Riedel and Andrew Mccallum
Advances in Neural Information Processing Systems 25, 2012


Query-Aware MCMC
Michael L. Wick and Andrew Mccallum
Advances in Neural Information Processing Systems 24, 2011


SampleRank: Training Factor Graphs with Atomic Gradients
Khashayar Rohanimanesh, Kedar Bellare, Aron Culotta, Andrew Mccallum and Michael L. Wick
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


High-Performance Semi-Supervised Learning using Discriminatively Constrained Generative Models
Gregory Druck and Andrew Mccallum
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Rethinking LDA: Why Priors Matter
Andrew Mccallum, David M. Mimno and Hanna M. Wallach
Advances in Neural Information Processing Systems 22, 2009


Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference
Khashayar Rohanimanesh, Sameer Singh, Andrew Mccallum and Michael J. Black
Advances in Neural Information Processing Systems 22, 2009


FACTORIE: Probabilistic Programming via Imperatively Defined Factor Graphs
Andrew Mccallum, Karl Schultz and Sameer Singh
Advances in Neural Information Processing Systems 22, 2009


Piecewise pseudolikelihood for efficient training of conditional random fields
Charles A. Sutton and Andrew Mccallum
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Mixtures of hierarchical topics with Pachinko allocation
David M. Mimno, Wei Li and Andrew Mccallum
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Simple, robust, scalable semi-supervised learning via expectation regularization
Gideon S. Mann and Andrew Mccallum
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data
Charles A. Sutton, Andrew Mccallum and Khashayar Rohanimanesh
Journal of Machine Learning Research, 2007


Pachinko allocation: DAG-structured mixture models of topic correlations
Wei Li and Andrew Mccallum
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006


Multi-way distributional clustering via pairwise interactions
Ron Bekkerman, Ran El-yaniv and Andrew Mccallum
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data
Charles A. Sutton, Khashayar Rohanimanesh and Andrew Mccallum
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Conditional Models of Identity Uncertainty with Application to Noun Coreference
Andrew Mccallum and Ben Wellner
Advances in Neural Information Processing Systems 17, 2004


Classification with Hybrid Generative/Discriminative Models
Rajat Raina, Yirong Shen, Andrew Mccallum and Andrew Y. Ng
Advances in Neural Information Processing Systems 16, 2003