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All publications by Russell Greiner
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Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification
Junfeng Wen, Chun-nam Yu and Russell Greiner
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Min-Max Problems on Factor Graphs
Siamak Ravanbakhsh, Christopher Srinivasa, Brendan Frey and Russell Greiner
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Augmentative Message Passing for Traveling Salesman Problem and Graph Partitioning
Siamak Ravanbakhsh, Reihaneh Rabbany and Russell Greiner
Advances in Neural Information Processing Systems 27, 2014


Online Learning with Costly Features and Labels
Navid Zolghadr, Gabor Bartok, Russell Greiner, András György and Csaba Szepesvari
Advances in Neural Information Processing Systems 26, 2013


A Generalized Loop Correction Method for Approximate Inference in Graphical Models
Siamak Ravanbakhsh, Russell Greiner and Chun-nam J. Yu
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Learning Patient-Specific Cancer Survival Distributions as a Sequence of Dependent Regressors
Hsiu-chin Lin, Vickie Baracos, Russell Greiner and Chun-nam J. Yu
Advances in Neural Information Processing Systems 24, 2011


Budgeted Distribution Learning of Belief Net Parameters
Liuyang Li, Barnabás Póczos, Csaba Szepesvári and Russell Greiner
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Learning when to stop thinking and do something!
Barnabás Póczos, Yasin Abbasi-yadkori, Csaba Szepesvári, Russell Greiner and Nathan R. Sturtevant
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Learning to segment from a few well-selected training images
Alireza Farhangfar, Russell Greiner and Csaba Szepesvári
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Using query-specific variance estimates to combine Bayesian classifiers
Chi-hoon Lee, Russell Greiner and Shaojun Wang
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006


Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields
Chi-hoon Lee, Shaojun Wang, Feng Jiao, Dale Schuurmans and Russell Greiner
Advances in Neural Information Processing Systems 19, 2006


Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale Schuurmans and Li Cheng
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005