| 2025 | ICLR | Extendable and Iterative Structure Learning Strategy for Bayesian Networks. | Hamid Kalantari, Russell Greiner, Pouria Ramazi |
| 2024 | ICML | Conformalized Survival Distributions: A Generic Post-Process to Increase Calibration. | Shiang Qi, Yakun Yu, Russell Greiner |
| 2023 | ICASSP | Exploring Language-Agnostic Speech Representations Using Domain Knowledge for Detecting Alzheimer's Dementia. | Zehra Shah, Shiang Qi, Fei Wang, Mahtab Farrokh, Mashrura Tasnim, Eleni Stroulia, Russell Greiner, Manos Plitsis, Athanasios Katsamanis |
| 2023 | ICML | An Effective Meaningful Way to Evaluate Survival Models. | Shiang Qi, Neeraj Kumar, Mahtab Farrokh, Weijie Sun, Li-Hao Kuan, Rajesh Ranganath, Ricardo Henao, Russell Greiner |
| 2023 | UAI | Copula-based deep survival models for dependent censoring. | Ali Hossein Gharari Foomani, Michael Cooper, Russell Greiner, Rahul G. Krishnan |
| 2021 | AISTATS | Sample efficient learning of image-based diagnostic classifiers via probabilistic labels. | Roberto Vega, Pouneh Gorji, Zichen Zhang, Xuebin Qin, Abhilash Rakkunedeth Hareendranathan, Jeevesh Kapur, Jacob L. Jaremko, Russell Greiner |
| 2020 | ICLR | Learning Disentangled Representations for CounterFactual Regression. | Negar Hassanpour, Russell Greiner |
| 2020 | ICML | Domain Aggregation Networks for Multi-Source Domain Adaptation. | Junfeng Wen, Russell Greiner, Dale Schuurmans |
| 2019 | BIBE | Ischemic Stroke Lesion Prediction in CT Perfusion Scans Using Multiple Parallel U-Nets Following by a Pixel-Level Classifier. | Mohsen Soltanpour, Russell Greiner, Pierre Boulanger, Brian Buck |
| 2019 | IJCAI | CounterFactual Regression with Importance Sampling Weights. | Negar Hassanpour, Russell Greiner |
| 2019 | IJCAI | Simultaneous Prediction Intervals for Patient-Specific Survival Curves. | Samuel Sokota, Ryan D'Orazio, Khurram Javed, Humza Haider, Russell Greiner |
| 2018 | AI | A Novel Evaluation Methodology for Assessing Off-Policy Learning Methods in Contextual Bandits. | Negar Hassanpour, Russell Greiner |
| 2018 | ICSE | Analyzing the effects of test driven development in GitHub. | Neil C. Borle, Meysam Feghhi, Eleni Stroulia, Russell Greiner, Abram Hindle |
| 2018 | MICCAI | Finding Effective Ways to (Machine) Learn fMRI-Based Classifiers from Multi-site Data. | Roberto Vega, Russell Greiner |
| 2016 | AISTATS | Stochastic Neural Networks with Monotonic Activation Functions. | Siamak Ravanbakhsh, Barnabs Pczos, Jeff G. Schneider, Dale Schuurmans, Russell Greiner |
| 2016 | ICML | Boolean Matrix Factorization and Noisy Completion via Message Passing. | Siamak Ravanbakhsh, Barnabs Pczos, Russell Greiner |
| 2015 | IJCAI | Correcting Covariate Shift with the Frank-Wolfe Algorithm. | Junfeng Wen, Russell Greiner, Dale Schuurmans |
| 2014 | AAAI | The Budgeted Biomarker Discovery Problem: A Variant of Association Studies. | Sheehan Khan, Russell Greiner |
| 2014 | ICIP | A robust convergence index filter for breast cancer cell segmentation. | Baidya Nath Saha, Amritpal Saini, Nilanjan Ray, Russell Greiner, Judith Hugh, Mauro Tambasco |
| 2014 | ICML | Min-Max Problems on Factor Graphs. | Siamak Ravanbakhsh, Christopher Srinivasa, Brendan J. Frey, Russell Greiner |
| 2014 | ICML | Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification. | Junfeng Wen, Chun-Nam Yu, Russell Greiner |
| 2013 | ICDM | Finding Discriminatory Genes: A Methodology for Validating Microarray Studies. | Sheehan Khan, Russell Greiner |
| 2013 | ISVC | Fully Automated Brain Tumor Segmentation Using Two MRI Modalities. | Mohamed Ben Salah, Idanis Diaz, Russell Greiner, Pierre Boulanger, Bret Hoehn, Albert Murtha |
| 2012 | ICML | A Generalized Loop Correction Method for Approximate Inference in Graphical Models. | Siamak Ravanbakhsh, Chun-Nam Yu, Russell Greiner |
| 2011 | PAKDD | Using Classifier-Based Nominal Imputation to Improve Machine Learning. | Xiaoyuan Su, Russell Greiner, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2010 | AAAI | A Cross-Entropy Method that Optimizes Partially Decomposable Problems: A New Way to Interpret NMR Spectra. | Siamak (Moshen) Ravanbakhsh, Barnabs Pczos, Russell Greiner |
| 2010 | AI | The IMAP Hybrid Method for Learning Gaussian Bayes Nets. | Oliver Schulte, Gustavo Frigo, Russell Greiner, Hassan Khosravi |
| 2010 | ICML | Budgeted Distribution Learning of Belief Net Parameters. | Liuyang Li, Barnabs Pczos, Csaba Szepesvri, Russell Greiner |
| 2009 | AIME | Segmentation of Lung Tumours in Positron Emission Tomography Scans: A Machine Learning Approach. | Aliaksei Kerhet, Cormac Small, Harvey Quon, Terence Riauka, Russell Greiner, Alexander McEwan, Wilson Roa |
| 2009 | CIDM | A new hybrid method for Bayesian network learning With dependency constraints. | Oliver Schulte, Gustavo Frigo, Russell Greiner, Wei Luo, Hassan Khosravi |
| 2009 | FlAIRS | VipBoost: A More Accurate Boosting Algorithm. | Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greiner |
| 2009 | ICML | Learning to segment from a few well-selected training images. | Alireza Farhangfar, Russell Greiner, Csaba Szepesvri |
| 2009 | ICML | Learning when to stop thinking and do something! | Barnabs Pczos, Yasin Abbasi-Yadkori, Csaba Szepesvri, Russell Greiner, Nathan R. Sturtevant |
| 2009 | UAI | Improved Mean and Variance Approximations for Belief Net Responses via Network Doubling. | Peter Hooper, Yasin Abbasi-Yadkori, Russell Greiner, Bret Hoehn |
| 2008 | AAAI | Constrained Classification on Structured Data. | Chi-Hoon Lee, Matthew R. G. Brown, Russell Greiner, Shaojun Wang, Albert Murtha |
| 2008 | FlAIRS | A Mixture Imputation-Boosted Collaborative Filter. | Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greiner |
| 2008 | ICIP | Supervised image segmentation via ground truth decomposition. | Ilya Levner, Russell Greiner, Hong Zhang |
| 2008 | ICMLA | Does Wikipedia Information Help Netflix Predictions? | John D. Lees-Miller, Fraser Anderson, Bret Hoehn, Russell Greiner |
| 2008 | ISAIM | A Fast Way to Produce Optimal Fixed-Depth Decision Trees. | Alireza Farhangfar, Russell Greiner, Martin Zinkevich |
| 2008 | ICTAI | Using Imputation Techniques to Help Learn Accurate Classifiers. | Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greiner |
| 2008 | MICCAI | Segmenting Brain Tumors Using Pseudo-Conditional Random Fields. | Chi-Hoon Lee, Shaojun Wang, Albert Murtha, Matthew R. G. Brown, Russell Greiner |
| 2008 | SAC | Imputation-boosted collaborative filtering using machine learning classifiers. | Xiaoyuan Su, Taghi M. Khoshgoftaar, Xingquan Zhu, Russell Greiner |
| 2008 | UAI | Speeding Up Planning in Markov Decision Processes via Automatically Constructed Abstraction. | Alejandro Isaza, Csaba Szepesvri, Vadim Bulitko, Russell Greiner |
| 2007 | COLT | Mind Change Optimal Learning of Bayes Net Structure. | Oliver Schulte, Wei Luo, Russell Greiner |
| 2007 | IJCAI | Optimistic Active-Learning Using Mutual Information. | Yuhong Guo, Russell Greiner |
| 2007 | PSB | Session Introduction. | David S. Wishart, Russell Greiner |
| 2006 | AAAI | Visual Explanation of Evidence with Additive Classifiers. | Brett Poulin, Roman Eisner, Duane Szafron, Paul Lu, Russell Greiner, David S. Wishart, Alona Fyshe, Brandon Pearcy, Cam Macdonell, John Anvik |
| 2006 | ACL | Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling. | Feng Jiao, Shaojun Wang, Chi-Hoon Lee, Russell Greiner, Dale Schuurmans |
| 2006 | AI | A Classification-Based Glioma Diffusion Model Using MRI Data. | Marianne Morris, Russell Greiner, Jrg Sander, Albert Murtha, Mark Schmidt |
| 2006 | ECCV | Learning to Detect Objects of Many Classes Using Binary Classifiers. | Ramana Isukapalli, Ahmed M. Elgammal, Russell Greiner |
| 2006 | ICML | Using query-specific variance estimates to combine Bayesian classifiers. | Chi-Hoon Lee, Russell Greiner, Shaojun Wang |
| 2006 | ICPR | Learning Policies for Efficiently Identifying Objects of Many Classes. | Ramana Isukapalli, Ahmed M. Elgammal, Russell Greiner |
| 2006 | IUI | Automatic construction of personalized customer interfaces. | Robert Price, Russell Greiner, Gerald Hubl, Alden Flatt |
| 2005 | AAAI | Discriminative Model Selection for Belief Net Structures. | Yuhong Guo, Russell Greiner |
| 2005 | AAAI | The Proteome Analyst Suite of Automated Function Prediction Tools. | Brett Poulin, Duane Szafron, Paul Lu, Russell Greiner, David S. Wishart, Roman Eisner, Alona Fyshe, Brandon Pearcy, Luca Pireddu |
| 2005 | AAAI | Goal-Directed Site-Independent Recommendations from Passive Observations. | Tingshao Zhu, Russell Greiner, Gerald Hubl, Kevin Jewell, Robert Price |
| 2005 | CIBCB | Improving Protein Function Prediction Using the Hierarchical Structure of the Gene Ontology. | Roman Eisner, Brett Poulin, Duane Szafron, Paul Lu, Russell Greiner |
| 2005 | ICML | Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields. | Shaojun Wang, Shaomin Wang, Russell Greiner, Dale Schuurmans, Li Cheng |
| 2005 | ICMLA | Segmenting brain tumors using alignment-based features. | Mark Schmidt, Ilya Levner, Russell Greiner, Albert Murtha, Aalo Bistritz |
| 2005 | IJCAI | Learning Coordination Classifiers. | Yuhong Guo, Russell Greiner, Dale Schuurmans |
| 2005 | IJCAI | Using Learned Browsing Behavior Models to Recommend Relevant Web Pages. | Tingshao Zhu, Russell Greiner, Gerald Hubl, Kevin Jewell, Robert Price |
| 2004 | COLT | The Budgeted Multi-armed Bandit Problem. | Omid Madani, Daniel J. Lizotte, Russell Greiner |
| 2004 | UAI | Active Model Selection. | Omid Madani, Daniel J. Lizotte, Russell Greiner |
| 2003 | IJCAI | Lookahead Pathologies for Single Agent Search. | Vadim Bulitko, Lihong Li, Russell Greiner, Ilya Levner |
| 2003 | IJCAI | Use of Off-line Dynamic Programming for Efficient Image Interpretation. | Ramana Isukapalli, Russell Greiner |
| 2003 | IJCAI | Predicting Web Information Content. | Tingshao Zhu, Russell Greiner, Gerald Hubl, Robert Price |
| 2003 | ICTAI | Discriminative Parameter Learning of General Bayesian Network Classifiers. | Bin Shen, Xiaoyuan Su, Russell Greiner, Petr Muslek, Corrine Cheng |
| 2003 | WWW | An Effective Complete-Web Recommender System. | Tingshao Zhu, Russell Greiner, Gerald Hubl |
| 2003 | UAI | Budgeted Learning of Naive-Bayes Classifiers. | Daniel J. Lizotte, Omid Madani, Russell Greiner |
| 2002 | AAAI | Optimal Depth-First Strategies for And-Or Trees. | Russell Greiner, Ryan Hayward, Michael Molloy |
| 2002 | AAAI | Structural Extension to Logistic Regression: Discriminative Parameter Learning of Belief Net Classifiers. | Russell Greiner, Wei Zhou |
| 2001 | AI | Learning Bayesian Belief Network Classifiers: Algorithms and System. | Jie Cheng, Russell Greiner |
| 2001 | IJCAI | Efficient Interpretation Policies. | Ramana Isukapalli, Russell Greiner |
| 2001 | ICRA | Efficient Car Recognition Policies. | Ramana Isukapalli, Russell Greiner |
| 2001 | UAI | Bayesian Error-Bars for Belief Net Inference. | Tim Van Allen, Russell Greiner, Peter Hooper |
| 2000 | AAAI | Predicting UNIX Command Lines: Adjusting to User Patterns. | Benjamin Korvemaker, Russell Greiner |
| 2000 | ICML | Model Selection Criteria for Learning Belief Nets: An Empirical Comparison. | Tim Van Allen, Russell Greiner |
| 1999 | UAI | Comparing Bayesian Network Classifiers. | Jie Cheng, Russell Greiner |
| 1997 | ICML | Why Experimentation can be better than "Perfect Guidance". | Tobias Scheffer, Russell Greiner, Christian Darken |
| 1997 | UAI | Learning Bayesian Nets that Perform Well. | Russell Greiner, Adam J. Grove, Dale Schuurmans |
| 1996 | ICML | Exploiting the Omission of Irrelevant Data. | Russell Greiner, Adam J. Grove, Alexander Kogan |
| 1996 | ICML | Learning Active Classifiers. | Russell Greiner, Adam J. Grove, Dan Roth |
| 1995 | COLT | Sequential PAC Learning. | Dale Schuurmans, Russell Greiner |
| 1995 | ICML | The Challenge of Revising an Impure Theory. | Russell Greiner |
| 1995 | IJCAI | The Complexity of Theory Revision. | Russell Greiner |
| 1995 | IJCAI | Practical PAC Learning. | Dale Schuurmans, Russell Greiner |
| 1994 | AAAI | Learning to Select Useful Landmarks. | Russell Greiner, Ramana Isukapalli |
| 1992 | AAAI | A Statistical Approach to Solving the EBL Utility Problem. | Russell Greiner, Igor Jurisica |
| 1992 | ECAI | Learning an Optimally Accurate Representation System. | Russell Greiner, Dale Schuurmans |
| 1992 | KR | Learning Useful Horn Approximations. | Russell Greiner, Dale Schuurmans |
| 1992 | PODS | Learning Efficient Query Processing Strategies. | Russell Greiner |
| 1991 | IJCAI | Measuring and Improving the Effectiveness of Representations. | Russell Greiner, Charles Elkan |
| 1991 | KR | Probably Approximately Optimal Derivation Strategies. | Russell Greiner, Pekka Orponen |
| 1990 | COLT | On the Sample Complexity of Finding Good Search Strategies. | Pekka Orponen, Russell Greiner |
| 1989 | ICML | Towards a Formal Analysis of EBL. | Russell Greiner |
| 1989 | IJCAI | Incorporating Redundant Learned Rules: A Preliminary Formal Analysis of EBL. | Russell Greiner, J. Likuski |
| 1988 | ICASSP | Signal abstractions in the machine analysis of radar signals for ice profiling. | S. Lee, Evangelos E. Milios, Russell Greiner, James R. Rossiter |
| 1983 | IJCAI | What's New? A Semantic Definition of Novelty. | Russell Greiner, Michael R. Genesereth |
| 1980 | AAAI | A Representation Language Language. | Russell Greiner, Douglas B. Lenat |