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Russell Greiner

University of Alberta

SIMLR: Machine Learning inside the SIR model for COVID-19 Forecasting


Jun 03, 2021
Roberto Vega, Leonardo Flores, Russell Greiner


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Sample Efficient Learning of Image-Based Diagnostic Classifiers Using Probabilistic Labels


Feb 11, 2021
Roberto Vega, Pouneh Gorji, Zichen Zhang, Xuebin Qin, Abhilash Rakkunedeth Hareendranathan, Jeevesh Kapur, Jacob L. Jaremko, Russell Greiner

* To appear in the Proceedings of the 24 th International Conference on Artificial Intelligence and Statistics (AISTATS) 2021, San Diego,California, USA. PMLR: Volume 130 

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Shared Space Transfer Learning for analyzing multi-site fMRI data


Oct 24, 2020
Muhammad Yousefnezhad, Alessandro Selvitella, Daoqiang Zhang, Andrew J. Greenshaw, Russell Greiner

* 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Vancouver, Canada. The Supplementary Material: https://www.yousefnezhad.com/publications/NeurIPS2020_Paper4157_SuppMat.zip 

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Reducing Selection Bias in Counterfactual Reasoning for Individual Treatment Effects Estimation


Dec 19, 2019
Zichen Zhang, Qingfeng Lan, Lei Ding, Yue Wang, Negar Hassanpour, Russell Greiner

* NeurIPS 2019 Workshop on "Do the right thing": machine learning and causal inference for improved decision making 

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Domain Aggregation Networks for Multi-Source Domain Adaptation


Sep 25, 2019
Junfeng Wen, Russell Greiner, Dale Schuurmans


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Simultaneous Prediction Intervals for Patient-Specific Survival Curves


Jun 25, 2019
Samuel Sokota, Ryan D'Orazio, Khurram Javed, Humza Haider, Russell Greiner

* 7 pages, 7 figures, IJCAI 19 

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The Challenge of Predicting Meal-to-meal Blood Glucose Concentrations for Patients with Type I Diabetes


Mar 29, 2019
Neil C. Borle, Edmond A. Ryan, Russell Greiner


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Gene Expression based Survival Prediction for Cancer Patients: A Topic Modeling Approach


Mar 25, 2019
Luke Kumar, Russell Greiner


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Effective Ways to Build and Evaluate Individual Survival Distributions


Nov 28, 2018
Humza Haider, Bret Hoehn, Sarah Davis, Russell Greiner

* 34 pages (main text), 12 figures 

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Learning Neural Markers of Schizophrenia Disorder Using Recurrent Neural Networks


Dec 01, 2017
Jumana Dakka, Pouya Bashivan, Mina Gheiratmand, Irina Rish, Shantenu Jha, Russell Greiner

* To be published as a workshop paper at NIPS 2017 Machine Learning for Health (ML4H) 

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Stochastic Neural Networks with Monotonic Activation Functions


Jul 22, 2016
Siamak Ravanbakhsh, Barnabas Poczos, Jeff Schneider, Dale Schuurmans, Russell Greiner

* AISTATS 2016 

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Boolean Matrix Factorization and Noisy Completion via Message Passing


Feb 04, 2016
Siamak Ravanbakhsh, Barnabas Poczos, Russell Greiner


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Revisiting Algebra and Complexity of Inference in Graphical Models


May 03, 2015
Siamak Ravanbakhsh, Russell Greiner


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Perturbed Message Passing for Constraint Satisfaction Problems


Feb 03, 2015
Siamak Ravanbakhsh, Russell Greiner

* JMLR 16(Jul):1249-1274, 2015 

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Accurate, fully-automated NMR spectral profiling for metabolomics


Sep 08, 2014
Siamak Ravanbakhsh, Philip Liu, Trent Bjorndahl, Rupasri Mandal, Jason R. Grant, Michael Wilson, Roman Eisner, Igor Sinelnikov, Xiaoyu Hu, Claudio Luchinat, Russell Greiner, David S. Wishart

* PLoS ONE 10(5): e0124219, 2015 

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Augmentative Message Passing for Traveling Salesman Problem and Graph Partitioning


Jun 04, 2014
Siamak Ravanbakhsh, Reihaneh Rabbany, Russell Greiner


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Training Restricted Boltzmann Machine by Perturbation


May 06, 2014
Siamak Ravanbakhsh, Russell Greiner, Brendan Frey


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Learning Bayesian Nets that Perform Well


Feb 06, 2013
Russell Greiner, Adam J. Grove, Dale Schuurmans

* Appears in Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence (UAI1997) 

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Comparing Bayesian Network Classifiers


Jan 23, 2013
Jie Cheng, Russell Greiner

* Appears in Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence (UAI1999) 

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Bayesian Error-Bars for Belief Net Inference


Jan 10, 2013
Tim Van Allen, Russell Greiner, Peter Hooper

* Appears in Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI2001) 

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Budgeted Learning of Naive-Bayes Classifiers


Oct 19, 2012
Daniel J. Lizotte, Omid Madani, Russell Greiner

* Appears in Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence (UAI2003) 

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Active Model Selection


Jul 11, 2012
Omid Madani, Daniel J. Lizotte, Russell Greiner

* Appears in Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence (UAI2004) 

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A Generalized Loop Correction Method for Approximate Inference in Graphical Models


Jun 18, 2012
Siamak Ravanbakhsh, Chun-Nam Yu, Russell Greiner

* ICML2012 

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Speeding Up Planning in Markov Decision Processes via Automatically Constructed Abstractions


Jun 13, 2012
Alejandro Isaza, Csaba Szepesvari, Vadim Bulitko, Russell Greiner

* Appears in Proceedings of the Twenty-Fourth Conference on Uncertainty in Artificial Intelligence (UAI2008) 

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Improved Mean and Variance Approximations for Belief Net Responses via Network Doubling


May 09, 2012
Peter Hooper, Yasin Abbasi-Yadkori, Russell Greiner, Bret Hoehn

* Appears in Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence (UAI2009) 

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