A Representation Language Language. - Russell Greiner; Douglas B. Lenat (AAAI, 1980)

What's New? A Semantic Definition of Novelty. - Russell Greiner; Michael R. Genesereth (IJCAI, 1983)

Learning by understanding analogies. - Russell Greiner (1985)

Signal abstractions in the machine analysis of radar signals for ice profiling. - S. Lee; Evangelos E. Milios; Russell Greiner; James R. Rossiter (ICASSP, 1988)

Learning by Understanding Analogies. - Russell Greiner (Artif. Intell., 1988)

Against the unjustified use of probabilities. - Russell Greiner (Comput. Intell., 1988)

A Review of Machine Learning at AAAI-87. - Russell Greiner (Mach. Learn., 1988)

Towards a Formal Analysis of EBL. - Russell Greiner (ML, 1989)

Incorporating Redundant Learned Rules: A Preliminary Formal Analysis of EBL. - Russell Greiner; J. Likuski (IJCAI, 1989)

A Correction to the Algorithm in Reiter's Theory of Diagnosis. - Russell Greiner; Barbara A. Smith; Ralph W. Wilkerson (Artif. Intell., 1989)

On the Sample Complexity of Finding Good Search Strategies. - Pekka Orponen; Russell Greiner (COLT, 1990)

Measuring and Improving the Effectiveness of Representations. - Russell Greiner; Charles Elkan (IJCAI, 1991)

Probably Approximately Optimal Derivation Strategies. - Russell Greiner; Pekka Orponen (KR, 1991)

Finding Optimal Derivation Strategies in Redundant Knowledge Bases. - Russell Greiner (Artif. Intell., 1991)

A Statistical Approach to Solving the EBL Utility Problem. - Russell Greiner; Igor Jurisica (AAAI, 1992)

Learning an Optimally Accurate Representation System. - Russell Greiner; Dale Schuurmans (ECAI Workshop on Knowledge Representation and Reasoning, 1992)

Learning Useful Horn Approximations. - Russell Greiner; Dale Schuurmans (KR, 1992)

Learning Efficient Query Processing Strategies. - Russell Greiner (PODS, 1992)

D. B. Lenat and R. V. Guha, Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project. - Charles Elkan; Russell Greiner (Artif. Intell., 1993)

Sequential PAC Learning. - Dale Schuurmans; Russell Greiner (COLT, 1995)

The Challenge of Revising an Impure Theory. - Russell Greiner (ICML, 1995)

The Complexity of Theory Revision. - Russell Greiner (IJCAI, 1995)

Practical PAC Learning. - Dale Schuurmans; Russell Greiner (IJCAI, 1995)

Exploiting the Omission of Irrelevant Data. - Russell Greiner; Adam J. Grove; Alexander Kogan (ICML, 1996)

Learning Active Classifiers. - Russell Greiner; Adam J. Grove; Dan Roth 001 (ICML, 1996)

PALO: A Probabilistic Hill-Climbing Algorithm. - Russell Greiner (Artif. Intell., 1996)

Probably Approximately Optimal Satisficing Strategies. - Russell Greiner; Pekka Orponen (Artif. Intell., 1996)

Learning to select useful landmarks. - Russell Greiner; Ramana Isukapalli (IEEE Trans. Syst. Man Cybern. Part B, 1996)

Why Experimentation can be better than "Perfect Guidance". - Tobias Scheffer; Russell Greiner; Christian Darken (ICML, 1997)

Learning Bayesian Nets that Perform Well. - Russell Greiner; Adam J. Grove; Dale Schuurmans (UAI, 1997)

Knowing what doesn't Matter: Exploiting the Omission of Irrelevant Data. - Russell Greiner; Adam J. Grove; Alexander Kogan (Artif. Intell., 1997)

The Relevance of Relevance (Editorial). - Devika Subramanian; Russell Greiner; Judea Pearl (Artif. Intell., 1997)

Comparing Bayesian Network Classifiers. - Jie Cheng; Russell Greiner (UAI, 1999)

The Complexity of Revising Logic Programs. - Russell Greiner (J. Log. Program., 1999)

Predicting UNIX Command Lines: Adjusting to User Patterns. - Benjamin Korvemaker; Russell Greiner (AAAI/IAAI, 2000)

Model Selection Criteria for Learning Belief Nets: An Empirical Comparison. - Tim Van Allen; Russell Greiner (ICML, 2000)

Learning Bayesian Belief Network Classifiers: Algorithms and System. - Jie Cheng; Russell Greiner (AI, 2001)

Efficient Car Recognition Policies. - Ramana Isukapalli; Russell Greiner (ICRA, 2001)

Efficient Interpretation Policies. - Ramana Isukapalli; Russell Greiner (IJCAI, 2001)

Bayesian Error-Bars for Belief Net Inference. - Tim Van Allen; Russell Greiner; Peter Hooper (UAI, 2001)

Efficient reasoning. - Russell Greiner; Christian Darken; N. Iwan Santoso (ACM Comput. Surv., 2001)

Optimal Depth-First Strategies for And-Or Trees. - Russell Greiner; Ryan Hayward; Michael Molloy 001 (AAAI/IAAI, 2002)

Structural Extension to Logistic Regression: Discriminative Parameter Learning of Belief Net Classifiers. - Russell Greiner; Wei Zhou (AAAI/IAAI, 2002)

Performance of Lookahead Control Policies in the Face of Abstractions and Approximations. - Ilya Levner; Vadim Bulitko; Omid Madani; Russell Greiner (SARA, 2002)

Learning Bayesian networks from data: An information-theory based approach. - Jie Cheng; Russell Greiner; Jonathan Kelly; David A. Bell; Weiru Liu (Artif. Intell., 2002)

Learning cost-sensitive active classifiers. - Russell Greiner; Adam J. Grove; Dan Roth 001 (Artif. Intell., 2002)

Towards Automated Creation of Image Interpretation Systems. - Ilya Levner; Vadim Bulitko; Lihong Li 001; Greg Lee; Russell Greiner (Australian Conference on Artificial Intelligence, 2003)

Discriminative Parameter Learning of General Bayesian Network Classifiers. - Bin Shen; Xiaoyuan Su; Russell Greiner; Petr Musílek; Corrine Cheng (ICTAI, 2003)

Lookahead Pathologies for Single Agent Search. - Vadim Bulitko; Lihong Li 001; Russell Greiner; Ilya Levner (IJCAI, 2003)

Use of Off-line Dynamic Programming for Efficient Image Interpretation. - Ramana Isukapalli; Russell Greiner (IJCAI, 2003)

Predicting Web Information Content. - Tingshao Zhu; Russell Greiner; Gerald Häubl; Robert Price (ITWP, 2003)

Budgeted Learning of Naive-Bayes Classifiers. - Daniel J. Lizotte; Omid Madani; Russell Greiner (UAI, 2003)

Learning a Model of a Web User's Interests. - Tingshao Zhu; Russell Greiner; Gerald Häubl (User Modeling, 2003)

An Effective Complete-Web Recommender System. - Tingshao Zhu; Russell Greiner; Gerald Häubl (WWW (Alternate Paper Tracks), 2003)

The Budgeted Multi-armed Bandit Problem. - Omid Madani; Daniel J. Lizotte; Russell Greiner (COLT, 2004)

Batch Reinforcement Learning with State Importance. - Lihong Li 001; Vadim Bulitko; Russell Greiner (ECML, 2004)

Active Model Selection. - Omid Madani; Daniel J. Lizotte; Russell Greiner (UAI, 2004)

Predicting subcellular localization of proteins using machine-learned classifiers. - Zhiyong Lu; Duane Szafron; Russell Greiner; Paul Lu; David S. Wishart; Brett Poulin; John Anvik; Cam Macdonell; Roman Eisner (Bioinform., 2004)

Proteome Analyst: custom predictions with explanations in a web-based tool for high-throughput proteome annotations. - Duane Szafron; Paul Lu; Russell Greiner; David S. Wishart; Brett Poulin; Roman Eisner; Zhiyong Lu; John Anvik; Cam Macdonell; Alona Fyshe; David Meeuwis (Nucleic Acids Res., 2004)

Discriminative Model Selection for Belief Net Structures. - Yuhong Guo; Russell Greiner (AAAI, 2005)

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 (AAAI, 2005)

Goal-Directed Site-Independent Recommendations from Passive Observations. - Tingshao Zhu; Russell Greiner; Gerald Häubl; Kevin Jewell; Robert Price (AAAI, 2005)

Learning a Dynamic Classification Method to Detect Faces and Identify Facial Expression. - Ramana Isukapalli; Ahmed M. Elgammal; Russell Greiner (AMFG, 2005)

Improving Protein Function Prediction Using the Hierarchical Structure of the Gene Ontology. - Roman Eisner; Brett Poulin; Duane Szafron; Paul Lu; Russell Greiner (CIBCB, 2005)

Segmenting Brain Tumors with Conditional Random Fields and Support Vector Machines. - Chi-Hoon Lee; Mark Schmidt 001; Albert Murtha; Aalo Bistritz; Jörg Sander 001; Russell Greiner (CVBIA, 2005)

Learning and Classifying Under Hard Budgets. - Aloak Kapoor; Russell Greiner (ECML, 2005)

Segmenting brain tumors using alignment-based features. - Mark Schmidt 001; Ilya Levner; Russell Greiner; Albert Murtha; Aalo Bistritz (ICMLA, 2005)

Learning Coordination Classifiers. - Yuhong Guo; Russell Greiner; Dale Schuurmans (IJCAI, 2005)

Using Learned Browsing Behavior Models to Recommend Relevant Web Pages. - Tingshao Zhu; Russell Greiner; Gerald Häubl; Kevin Jewell; Robert Price (IJCAI, 2005)

Support Vector Random Fields for Spatial Classification. - Chi-Hoon Lee; Russell Greiner; Mark Schmidt 001 (PKDD, 2005)

Off-line Evaluation of Recommendation Functions. - Tingshao Zhu; Russell Greiner; Gerald Häubl; Kevin Jewell; Robert Price (User Modeling, 2005)

Structural Extension to Logistic Regression: Discriminative Parameter Learning of Belief Net Classifiers. - Russell Greiner; Xiaoyuan Su; Bin Shen; Wei Zhou (Mach. Learn., 2005)

BASys: a web server for automated bacterial genome annotation. - Gary H. Van Domselaar; Paul Stothard; Savita Shrivastava; Joseph A. Cruz; Anchi Guo; Xiaoli Dong; Paul Lu; Duane Szafron; Russell Greiner; David S. Wishart (Nucleic Acids Res., 2005)

PA-GOSUB: a searchable database of model organism protein sequences with their predicted Gene Ontology molecular function and subcellular localization. - Paul Lu; Duane Szafron; Russell Greiner; David S. Wishart; Alona Fyshe; Brandon Pearcy; Brett Poulin; Roman Eisner; Danny Ngo; Nicholas Lamb (Nucleic Acids Res., 2005)

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 (AAAI, 2006)

Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling. - Feng Jiao; Shaojun Wang; Chi-Hoon Lee; Russell Greiner; Dale Schuurmans (ACL, 2006)

A Classification-Based Glioma Diffusion Model Using MRI Data. - Marianne Morris; Russell Greiner; Jörg Sander 001; Albert Murtha; Mark Schmidt 001 (Canadian AI, 2006)

Learning to Detect Objects of Many Classes Using Binary Classifiers. - Ramana Isukapalli; Ahmed M. Elgammal; Russell Greiner (ECCV (1), 2006)

Learning to Identify Facial Expression During Detection Using Markov Decision Process. - Ramana Isukapalli; Ahmed M. Elgammal; Russell Greiner (FGR, 2006)

Stochastic Analysis of Lexical and Semantic Enhanced Structural Language Model. - Shaojun Wang; Shaomin Wang; Li Cheng 001; Russell Greiner; Dale Schuurmans (ICGI, 2006)

Using query-specific variance estimates to combine Bayesian classifiers. - Chi-Hoon Lee; Russell Greiner; Shaojun Wang (ICML, 2006)

Learning Policies for Efficiently Identifying Objects of Many Classes. - Ramana Isukapalli; Ahmed M. Elgammal; Russell Greiner (ICPR (3), 2006)

Automatic construction of personalized customer interfaces. - Robert Price; Russell Greiner; Gerald Häubl; Alden Flatt (IUI, 2006)

Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields. - Chi-Hoon Lee; Shaojun Wang; Feng Jiao; Dale Schuurmans; Russell Greiner (NIPS, 2006)

Information Marginalization on Subgraphs. - Jiayuan Huang; Tingshao Zhu; Russell Greiner; Dengyong Zhou; Dale Schuurmans (PKDD, 2006)

Efficient Spatial Classification Using Decoupled Conditional Random Fields. - Chi-Hoon Lee; Russell Greiner; Osmar R. Zaïane (PKDD, 2006)

Finding optimal satisficing strategies for and-or trees. - Russell Greiner; Ryan Hayward; Magdalena Jankowska; Michael Molloy 001 (Artif. Intell., 2006)

Learning a Classification-based Glioma Growth Model Using MRI Data. - Marianne Morris; Russell Greiner; Jörg Sander 001; Albert Murtha; Mark Schmidt 001 (J. Comput., 2006)

The Path-A metabolic pathway prediction web server. - Luca Pireddu; Duane Szafron; Paul Lu; Russell Greiner (Nucleic Acids Res., 2006)

Mind Change Optimal Learning of Bayes Net Structure. - Oliver Schulte; Wei Luo 001; Russell Greiner (COLT, 2007)

Optimistic Active-Learning Using Mutual Information. - Yuhong Guo; Russell Greiner (IJCAI, 2007)

Session Introduction. - David S. Wishart; Russell Greiner (Pacific Symposium on Biocomputing, 2007)

Hybrid Collaborative Filtering Algorithms Using a Mixture of Experts. - Xiaoyuan Su; Russell Greiner; Taghi M. Khoshgoftaar; Xingquan Zhu 001 (Web Intelligence, 2007)

Focus of Attention in Reinforcement Learning. - Lihong Li 001; Vadim Bulitko; Russell Greiner (J. Univers. Comput. Sci., 2007)

HMDB: the Human Metabolome Database. - David S. Wishart; Dan Tzur; Craig Knox; Roman Eisner; Anchi Guo; Nelson Young; Dean Cheng; Kevin Jewell; David Arndt; Summit Sawhney; Chris Fung; Lisa Nikolai; et al. (Nucleic Acids Res., 2007)

Constrained Classification on Structured Data. - Chi-Hoon Lee; Matthew R. G. Brown; Russell Greiner; Shaojun Wang; Albert Murtha (AAAI, 2008)

A Cover-Based Approach to Multi-Agent Moving Target Pursuit. - Alejandro Isaza; Jieshan Lu; Vadim Bulitko; Russell Greiner (AIIDE, 2008)

A Mixture Imputation-Boosted Collaborative Filter. - Xiaoyuan Su; Taghi M. Khoshgoftaar; Russell Greiner (FLAIRS, 2008)

Supervised image segmentation via ground truth decomposition. - Ilya Levner; Russell Greiner; Hong Zhang 013 (ICIP, 2008)

Does Wikipedia Information Help Netflix Predictions? - John D. Lees-Miller; Fraser Anderson; Bret Hoehn; Russell Greiner (ICMLA, 2008)

Using Imputation Techniques to Help Learn Accurate Classifiers. - Xiaoyuan Su; Taghi M. Khoshgoftaar; Russell Greiner (ICTAI (1), 2008)

A Fast Way to Produce Optimal Fixed-Depth Decision Trees. - Alireza Farhangfar; Russell Greiner; Martin Zinkevich (ISAIM, 2008)

Segmenting Brain Tumors Using Pseudo-Conditional Random Fields. - Chi-Hoon Lee; Shaojun Wang; Albert Murtha; Matthew R. G. Brown; Russell Greiner (MICCAI (1), 2008)

Imputation-boosted collaborative filtering using machine learning classifiers. - Xiaoyuan Su; Taghi M. Khoshgoftaar; Xingquan Zhu 001; Russell Greiner (SAC, 2008)

Speeding Up Planning in Markov Decision Processes via Automatically Constructed Abstraction. - Alejandro Isaza; Csaba Szepesvári; Vadim Bulitko; Russell Greiner (UAI, 2008)

Imputed Neighborhood Based Collaborative Filtering. - Xiaoyuan Su; Taghi M. Khoshgoftaar; Russell Greiner (Web Intelligence, 2008)

Quantifying the uncertainty of a belief net response: Bayesian error-bars for belief net inference. - Tim Van Allen; Ajit Singh; Russell Greiner; Peter Hooper (Artif. Intell., 2008)

Improving subcellular localization prediction using text classification and the gene ontology. - Alona Fyshe; Yifeng Liu 001; Duane Szafron; Russell Greiner; Paul Lu (Bioinform., 2008)

Heterogeneous Stacking for Classification-Driven Watershed Segmentation. - Ilya Levner; Hong Zhang 013; Russell Greiner (EURASIP J. Adv. Signal Process., 2008)

Clustering high dimensional data: A graph-based relaxed optimization approach. - Chi-Hoon Lee; Osmar R. Zaïane; Ho-Hyun Park; Jiayuan Huang; Russell Greiner (Inf. Sci., 2008)

LILAC - Learn from Internet: Log, Annotation, and Content. - Tingshao Zhu; Russell Greiner; Bin Hu (AAAI Spring Symposium: Experimental Design for Real-World Systems, 2009)

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 (AIME, 2009)

A new hybrid method for Bayesian network learning With dependency constraints. - Oliver Schulte; Gustavo Frigo; Russell Greiner; Wei Luo 001; Hassan Khosravi (CIDM, 2009)

VipBoost: A More Accurate Boosting Algorithm. - Xiaoyuan Su; Taghi M. Khoshgoftaar; Russell Greiner (FLAIRS, 2009)

Learning to segment from a few well-selected training images. - Alireza Farhangfar; Russell Greiner; Csaba Szepesvári (ICML, 2009)

Learning when to stop thinking and do something! - Barnabás Póczos; Yasin Abbasi-Yadkori; Csaba Szepesvári; Russell Greiner; Nathan R. Sturtevant (ICML, 2009)

Improved Mean and Variance Approximations for Belief Net Responses via Network Doubling. - Peter Hooper; Yasin Abbasi-Yadkori; Russell Greiner; Bret Hoehn (UAI, 2009)

Predicting homologous signaling pathways using machine learning. - Babak Bostan; Russell Greiner; Duane Szafron; Paul Lu (Bioinform., 2009)

Making an accurate classifier ensemble by voting on classifications from imputed learning sets. - Xiaoyuan Su; Taghi M. Khoshgoftaar; Russell Greiner (Int. J. Inf. Decis. Sci., 2009)

HMDB: a knowledgebase for the human metabolome. - David S. Wishart; Craig Knox; Anchi Guo; Roman Eisner; Nelson Young; Bijaya Gautam; David D. Hau; Nick Psychogios; Edison Dong; Souhaila Bouatra; Rupasri Mandal; Igor Sinelnikov; et al. (Nucleic Acids Res., 2009)

A Cross-Entropy Method that Optimizes Partially Decomposable Problems: A New Way to Interpret NMR Spectra. - Siamak (Moshen) Ravanbakhsh; Barnabás Póczos; Russell Greiner (AAAI, 2010)

The IMAP Hybrid Method for Learning Gaussian Bayes Nets. - Oliver Schulte; Gustavo Frigo; Russell Greiner; Hassan Khosravi (Canadian AI, 2010)

Budgeted Distribution Learning of Belief Net Parameters. - Liuyang Li; Barnabás Póczos; Csaba Szepesvári; Russell Greiner (ICML, 2010)

Mind change optimal learning of Bayes net structure from dependency and independency data. - Oliver Schulte; Wei Luo 001; Russell Greiner (Inf. Comput., 2010)

A critical review of the effects of de-noising algorithms on MRI brain tumor segmentation. - Idanis Diaz; Pierre Boulanger; Russell Greiner; Albert Murtha (EMBC, 2011)

Learning Patient-Specific Cancer Survival Distributions as a Sequence of Dependent Regressors. - Chun-Nam Yu; Russell Greiner; Hsiu-Chin Lin; Vickie Baracos (NIPS, 2011)

Using Classifier-Based Nominal Imputation to Improve Machine Learning. - Xiaoyuan Su; Russell Greiner; Taghi M. Khoshgoftaar; Amri Napolitano (PAKDD (1), 2011)

A Generalized Loop Correction Method for Approximate Inference in Graphical Models. - Siamak Ravanbakhsh; Chun-Nam Yu; Russell Greiner (ICML, 2012)

Quick detection of brain tumors and edemas: A bounding box method using symmetry. - Baidya Nath Saha; Nilanjan Ray; Russell Greiner; Albert Murtha; Hong Zhang 013 (Comput. Medical Imaging Graph., 2012)

Speeding Up Planning in Markov Decision Processes via Automatically Constructed Abstractions - Alejandro Isaza; Csaba Szepesvári; Vadim Bulitko; Russell Greiner (CoRR, 2012)

Learning to predict ice accretion on electric power lines. - Ashkan Zarnani; Petr Musílek; Xiaoyu Shi; Xiaodi Ke; Hua He; Russell Greiner (Eng. Appl. Artif. Intell., 2012)

Combining gene expression and interaction network data to improve kidney lesion score prediction. - Davoud Moulavi; Mohsen Hajiloo; Jörg Sander 001; Philip F. Halloran; Russell Greiner (Int. J. Bioinform. Res. Appl., 2012)

An experimental methodology for response surface optimization methods. - Daniel J. Lizotte; Russell Greiner; Dale Schuurmans (J. Glob. Optim., 2012)

Predicting Army Combat Outcomes in StarCraft. - Marius Stanescu; Sergio Poo Hernandez; Graham Erickson; Russell Greiner; Michael Buro (AIIDE, 2013)

An automatic brain tumor segmentation tool. - Idanis Diaz; Pierre Boulanger; Russell Greiner; Bret Hoehn; Lindsay Rowe; Albert Murtha (EMBC, 2013)

Finding Discriminatory Genes: A Methodology for Validating Microarray Studies. - Sheehan Khan; Russell Greiner (ICDM Workshops, 2013)

Fully Automated Brain Tumor Segmentation Using Two MRI Modalities. - Mohamed Ben Salah; Idanis Diaz; Russell Greiner; Pierre Boulanger; Bret Hoehn; Albert Murtha (ISVC (1), 2013)

Online Learning with Costly Features and Labels. - Navid Zolghadr; Gábor Bartók; Russell Greiner; András György 001; Csaba Szepesvári (NIPS, 2013)

Breast cancer prediction using genome wide single nucleotide polymorphism data. - Mohsen Hajiloo; Babak Damavandi; Metanat HooshSadat; Farzad Sangi; John R. Mackey; Carol E. Cass; Russell Greiner; Sambasivarao Damaraju (BMC Bioinform., 2013)

ETHNOPRED: a novel machine learning method for accurate continental and sub-continental ancestry identification and population stratification correction. - Mohsen Hajiloo; Yadav Sapkota; John R. Mackey; Paula Robson; Russell Greiner; Sambasivarao Damaraju (BMC Bioinform., 2013)

Exploiting Syntactic, Semantic, and Lexical Regularities in Language Modeling via Directed Markov Random Fields. - Shaojun Wang; Shaomin Wang; Li Cheng 001; Russell Greiner; Dale Schuurmans (Comput. Intell., 2013)

Competitive Fragmentation Modeling of ESI-MS/MS spectra for metabolite identification. - Felicity Allen; Russell Greiner; David S. Wishart (CoRR, 2013)

Consistency and Generalization Bounds for Maximum Entropy Density Estimation. - Shaojun Wang; Russell Greiner; Shaomin Wang (Entropy, 2013)

HMDB 3.0 - The Human Metabolome Database in 2013. - David S. Wishart; Timothy Jewison; Anchi Guo; Michael Wilson 002; Craig Knox; Yifeng Liu 001; Yannick Djoumbou; Rupasri Mandal; Farid Aziat; Edison Dong; Souhaila Bouatra; Igor Sinelnikov; et al. (Nucleic Acids Res., 2013)

The Budgeted Biomarker Discovery Problem: A Variant of Association Studies. - Sheehan Khan; Russell Greiner (AAAI Workshop: Modern Artificial Intelligence for Health Analytics, 2014)

Budgeted transcript discovery: A framework for joint exploration and validation studies. - Sheehan Khan; Russell Greiner (BIBM, 2014)

A robust convergence index filter for breast cancer cell segmentation. - Baidya Nath Saha; Amritpal Saini; Nilanjan Ray; Russell Greiner; Judith Hugh; Mauro Tambasco (ICIP, 2014)

Min-Max Problems on Factor Graphs. - Siamak Ravanbakhsh; Christopher Srinivasa; Brendan J. Frey; Russell Greiner (ICML, 2014)

Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification. - Junfeng Wen; Chun-Nam Yu; Russell Greiner (ICML, 2014)

Budgeted Learning for Developing Personalized Treatment. - Kun Deng; Russ Greiner; Susan A. Murphy (ICMLA, 2014)

Augmentative Message Passing for Traveling Salesman Problem and Graph Partitioning. - Siamak Ravanbakhsh; Reihaneh Rabbany; Russell Greiner (NIPS, 2014)

Algebra of inference in graphical models revisited. - Siamak Ravanbakhsh; Russell Greiner (CoRR, 2014)

Training Restricted Boltzmann Machine by Perturbation. - Siamak Ravanbakhsh; Russell Greiner; Brendan J. Frey (CoRR, 2014)

Accurate, fully-automated NMR spectral profiling for metabolomics. - Siamak Ravanbakhsh; Philip Liu; Trent C. Bjorndahl; Rupasri Mandal; Jason R. Grant; Michael Wilson 002; Roman Eisner; Igor Sinelnikov; Xiaoyu Hu; Claudio Luchinat; Russell Greiner; David S. Wishart (CoRR, 2014)

CFM-ID: a web server for annotation, spectrum prediction and metabolite identification from tandem mass spectra. - Felicity Allen; Allison Pon; Michael Wilson 002; Russell Greiner; David S. Wishart (Nucleic Acids Res., 2014)

A system-call based model of software energy consumption without hardware instrumentation. - Shaiful Alam Chowdhury; Luke N. Kumar; Md. Toukir Imam; Mohomed Shazan Mohomed Jabbar; Varun Sapra; Karan Aggarwal; Abram Hindle; Russell Greiner (IGSC, 2015)

Correcting Covariate Shift with the Frank-Wolfe Algorithm. - Junfeng Wen; Russell Greiner; Dale Schuurmans (IJCAI, 2015)

Boolean Matrix Factorization and Completion via Message Passing. - Siamak Ravanbakhsh; Russell Greiner (CoRR, 2015)

Perturbed message passing for constraint satisfaction problems. - Siamak Ravanbakhsh; Russell Greiner (J. Mach. Learn. Res., 2015)

Stochastic Neural Networks with Monotonic Activation Functions. - Siamak Ravanbakhsh; Barnabás Póczos; Jeff G. Schneider; Dale Schuurmans; Russell Greiner (AISTATS, 2016)

Boolean Matrix Factorization and Noisy Completion via Message Passing. - Siamak Ravanbakhsh; Barnabás Póczos; Russell Greiner (ICML, 2016)

ClassyFire: automated chemical classification with a comprehensive, computable taxonomy. - Yannick Djoumbou; Roman Eisner; Craig Knox; Leonid L. Chepelev; Janna Hastings; Gareth I. Owen; Eoin Fahy; Christoph Steinbeck; Shankar Subramanian; Evan Bolton; Russell Greiner; David S. Wishart (J. Cheminformatics, 2016)

Deep Green: Modelling Time-Series of Software Energy Consumption. - Stephen Romansky; Neil C. Borle; Shaiful Alam Chowdhury; Abram Hindle; Russell Greiner (ICSME, 2017)

Learning discriminative functional network features of schizophrenia. - Mina Gheiratmand; Irina Rish; Guillermo A. Cecchi; Matthew R. G. Brown; Russell Greiner; Pouya Bashivan; Pablo Polosecki; Serdar M. Dursun (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2017)

Assessment of feature selection and classification methods for recognizing motor imagery tasks from electroencephalographic signals. - Roberto Vega; Touqir Sajed; Kory Wallace Mathewson; Kriti Khare; Patrick M. Pilarski; Russell Greiner; Gildardo Sánchez-Ante; Javier Mauricio Antelis (Artif. Intell. Res., 2017)

Learning Neural Markers of Schizophrenia Disorder Using Recurrent Neural Networks. - Jumana Dakka; Pouya Bashivan; Mina Gheiratmand; Irina Rish; Shantenu Jha; Russell Greiner (CoRR, 2017)

Detecting duplicate bug reports with software engineering domain knowledge. - Karan Aggarwal; Finbarr Timbers; Tanner Rutgers; Abram Hindle; Eleni Stroulia; Russell Greiner (J. Softw. Evol. Process., 2017)

A Novel Evaluation Methodology for Assessing Off-Policy Learning Methods in Contextual Bandits. - Negar Hassanpour; Russell Greiner (Canadian AI, 2018)

Finding Effective Ways to (Machine) Learn fMRI-Based Classifiers from Multi-site Data. - Roberto Vega; Russell Greiner (MLCN/DLF/iMIMIC@MICCAI, 2018)

Analyzing the effects of test driven development in GitHub. - Neil C. Borle; Meysam Feghhi; Eleni Stroulia; Russell Greiner; Abram Hindle (Empir. Softw. Eng., 2018)

CypReact: A Software Tool for in Silico Reactant Prediction for Human Cytochrome P450 Enzymes. - Siyang Tian; Yannick Djoumbou Feunang; Russell Greiner; David S. Wishart (J. Chem. Inf. Model., 2018)

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 (BIBE, 2019)

CounterFactual Regression with Importance Sampling Weights. - Negar Hassanpour; Russell Greiner (IJCAI, 2019)

Simultaneous Prediction Intervals for Patient-Specific Survival Curves. - Samuel Sokota; Ryan D'Orazio; Khurram Javed; Humza Haider; Russell Greiner (IJCAI, 2019)

Learning Macroscopic Brain Connectomes via Group-Sparse Factorization. - Farzane Aminmansour; Andrew Patterson; Lei Le; Yisu Peng; Daniel Mitchell; Franco Pestilli; Cesar F. Caiafa; Russell Greiner; Martha White (NeurIPS, 2019)

A simple classification framework for predicting Alzheimer's disease from region-based grey matter volume and APOE genotype status. - Reyhaneh Ghoreishiamiri; Graham Little; Matthew R. G. Brown; Russell Greiner (Artif. Intell. Res., 2019)

Gene Expression based Survival Prediction for Cancer Patients: A Topic Modeling Approach. - Luke N. Kumar; Russell Greiner (CoRR, 2019)

The Challenge of Predicting Meal-to-meal Blood Glucose Concentrations for Patients with Type I Diabetes. - Neil C. Borle; Edmond A. Ryan; Russell Greiner (CoRR, 2019)

Predicting the Long-Term Outcomes of Biologics in Psoriasis Patients Using Machine Learning. - Seyedeh Sepideh Emam; Amy X. Du; Philip Surmanowicz; Simon F. Thomsen; Russ Greiner; Robert Gniadecki (CoRR, 2019)

Reducing Selection Bias in Counterfactual Reasoning for Individual Treatment Effects Estimation. - Zichen Zhang 001; Qingfeng Lan; Lei Ding; Yue Wang; Negar Hassanpour; Russell Greiner (CoRR, 2019)

BioTransformer: a comprehensive computational tool for small molecule metabolism prediction and metabolite identification. - Yannick Djoumbou Feunang; Jarlei Fiamoncini; Alberto Gil-de-la-Fuente; Russell Greiner; Claudine Manach; David S. Wishart (J. Cheminformatics, 2019)

Low-Dimensional Perturb-and-MAP Approach for Learning Restricted Boltzmann Machines. - Jakub M. Tomczak; Szymon Zareba; Siamak Ravanbakhsh; Russell Greiner (Neural Process. Lett., 2019)

Learning Disentangled Representations for CounterFactual Regression. - Negar Hassanpour; Russell Greiner (ICLR, 2020)

Domain Aggregation Networks for Multi-Source Domain Adaptation. - Junfeng Wen; Russell Greiner; Dale Schuurmans (ICML, 2020)

Shared Space Transfer Learning for analyzing multi-site fMRI data. - Muhammad Yousefnezhad; Alessandro Selvitella; Daoqiang Zhang; Andrew J. Greenshaw; Russell Greiner (NeurIPS, 2020)

Effective Ways to Build and Evaluate Individual Survival Distributions. - Humza Haider; Bret Hoehn; Sarah Davis; Russell Greiner (J. Mach. Learn. Res., 2020)

Sample efficient learning of image-based diagnostic classifiers via probabilistic labels. - Roberto Vega; Pouneh Gorji; Zichen Zhang 001; Xuebin Qin; Abhilash Rakkunedeth Hareendranathan; Jeevesh Kapur; Jacob L. Jaremko; Russell Greiner (AISTATS, 2021)

Preface: AAAI Spring Symposium on Survival Prediction - Algorithms, Challenges, and Applications 2021. - Russell Greiner; Neeraj Kumar 002; Thomas Alexander Gerds; Mihaela van der Schaar (SPACA, 2021)

Improving the Calibration of Long Term Predictions of Heart Failure Rehospitalizations using Medical Concept Embedding. - Sunil Vasu Kalmady; Weijie Sun 004; Justin A. Ezekowitz; Nowell Fine; Jonathan Howlett; Anamaria Savu; Russ Greiner; Padma Kaul (SPACA, 2021)

Finding Relevant Features for Different Times in Survival Prediction by Discrete Hazard Bayesian Network. - Li-Hao Kuan; Russell Greiner (SPACA, 2021)

Identification of spectral features in the longwave infrared (LWIR) spectra of leaves for the discrimination of tropical dry forest tree species. - Yaqian Long; Benoit Rivard; Arturo Sanchez-Azofeifa; Russell Greiner; Dominica E. Harrison; Sen Jia 001 (Int. J. Appl. Earth Obs. Geoinformation, 2021)

Improvement of automatic ischemic stroke lesion segmentation in CT perfusion maps using a learned deep neural network. - Mohsen Soltanpour; Russ Greiner; Pierre Boulanger; Brian Buck (Comput. Biol. Medicine, 2021)

Sample Efficient Learning of Image-Based Diagnostic Classifiers Using Probabilistic Labels. - Roberto Vega; Pouneh Gorji; Zichen Zhang 001; Xuebin Qin; Abhilash Rakkunedeth Hareendranathan; Jeevesh Kapur; Jacob L. Jaremko; Russell Greiner (CoRR, 2021)

SIMLR: Machine Learning inside the SIR model for COVID-19 Forecasting. - Roberto Vega; Leonardo Flores; Russell Greiner (CoRR, 2021)

Variational Auto-Encoder Architectures that Excel at Causal Inference. - Negar Hassanpour; Russell Greiner (CoRR, 2021)

Learning Language and Acoustic Models for Identifying Alzheimer's Dementia From Speech. - Zehra Shah; Jeffrey Sawalha; Mashrura Tasnim; Shiang Qi; Eleni Stroulia; Russell Greiner (Frontiers Comput. Sci., 2021)

The challenge of predicting blood glucose concentration changes in patients with type I diabetes. - Neil C. Borle; Edmond A. Ryan; Russell Greiner (Health Informatics J., 2021)

CyProduct: A Software Tool for Accurately Predicting the Byproducts of Human Cytochrome P450 Metabolism. - Siyang Tian; Xuan Cao; Russell Greiner; Carin Li; Anchi Guo; David S. Wishart (J. Chem. Inf. Model., 2021)

A deep generative model enables automated structure elucidation of novel psychoactive substances. - Michael A. Skinnider; Fei Wang 062; Daniel Pasin; Russell Greiner; Leonard J. Foster; Petur W. Dalsgaard; David S. Wishart (Nat. Mach. Intell., 2021)

Domain-shift adaptation via linear transformations. - Roberto Vega; Russell Greiner (CoRR, 2022)

ECG for high-throughput screening of multiple diseases: Proof-of-concept using multi-diagnosis deep learning from population-based datasets. - Weijie Sun 004; Sunil Vasu Kalmady; Amir Salimi; Nariman Sepehrvand; Eric Ly; Abram Hindle; Russell Greiner; Padma Kaul (CoRR, 2022)

Ischemic Stroke Lesion Prediction using imbalanced Temporal Deep Gaussian Process (iTDGP). - Mohsen Soltanpour; Muhammad Yousefnezhad; Russ Greiner; Pierre Boulanger; Brian Buck (CoRR, 2022)

Improving ECG-based COVID-19 diagnosis and mortality predictions using pre-pandemic medical records at population-scale. - Weijie Sun 004; Sunil Vasu Kalmady; Nariman Sepehrvand; Luan Manh Chu; Zihan Wang 007; Amir Salimi; Abram Hindle; Russell Greiner; Padma Kaul (CoRR, 2022)

Multi-Source Domain Adaptation Techniques for Mitigating Batch Effects: A Comparative Study. - Rohan Panda; Sunil Vasu Kalmady; Russell Greiner (Frontiers Neuroinformatics, 2022)

Editorial: Multi-site neuroimage analysis: Domain adaptation and batch effects. - Muhammad Yousefnezhad; Daoqiang Zhang; Andrew J. Greenshaw; Russell Greiner (Frontiers Neuroinformatics, 2022)

CFM-ID 4.0 - a web server for accurate MS-based metabolite identification. - Fei Wang 062; Dana Allen; Siyang Tian; Eponine Oler; Vasuk Gautam; Russell Greiner; Thomas O. Metz; David S. Wishart (Nucleic Acids Res., 2022)

HMDB 5.0: the Human Metabolome Database for 2022. - David S. Wishart; Anchi Guo; Eponine Oler; Fei Wang 062; Afia Anjum; Harrison Peters; Raynard Dizon; Zinat Sayeeda; Siyang Tian; Brian L. Lee; Mark V. Berjanskii; Robert Mah; et al. (Nucleic Acids Res., 2022)

BioTransformer 3.0 - a web server for accurately predicting metabolic transformation products. - David S. Wishart; Siyang Tian; Dana Allen; Eponine Oler; Harrison Peters; Vicki W. Lui; Vasuk Gautam; Yannick Djoumbou Feunang; Russell Greiner; Thomas O. Metz (Nucleic Acids Res., 2022)

Exploring Language-Agnostic Speech Representations Using Domain Knowledge for Detecting Alzheimer's Dementia. - Zehra Shah; Shiang Qi; Fei Wang 062; Mahtab Farrokh; Mashrura Tasnim; Eleni Stroulia; Russell Greiner; Manos Plitsis; Athanasios Katsamanis (ICASSP, 2023)

An Effective Meaningful Way to Evaluate Survival Models. - Shiang Qi; Neeraj Kumar 002; Mahtab Farrokh; Weijie Sun 004; Li-Hao Kuan; Rajesh Ranganath; Ricardo Henao; Russell Greiner (ICML, 2023)

Using temporal GAN to translate the current CTP scan to follow-up MRI, for predicting final acute ischemic stroke lesions. - Mohsen Soltanpour; Muhammad Yousefnezhad; Russ Greiner; Pierre Boulanger; Brian Buck (Computer-Aided Diagnosis, 2023)

Supervised Electrocardiogram(ECG) Features Outperform Knowledge-based And Unsupervised Features In Individualized Survival Prediction. - Yousef Nademi; Sunil Vasu Kalmady; Weijie Sun 004; Shiang Qi; Abram Hindle; Padma Kaul; Russell Greiner (ML4H@NeurIPS, 2023)

Generative Data by β-Variational Autoencoders Help Build Stronger Classifiers: ECG Use Case. - Yousef Nademi; Sunil Vasu Kalmady; Weijie Sun 004; Amir Salimi; Abram Hindle; Padma Kaul; Russell Greiner (SIPAIM, 2023)

Copula-based deep survival models for dependent censoring. - Ali Hossein Gharari Foomani; Michael Cooper; Russell Greiner; Rahul G. Krishnan (UAI, 2023)

Modeling and Forecasting COVID-19 Cases using Latent Subpopulations. - Roberto Vega; Zehra Shah; Pouria Ramazi; Russell Greiner (CoRR, 2023)

Towards artificial intelligence-based learning health system for population-level mortality prediction using electrocardiograms. - Weijie Sun 004; Sunil Vasu Kalmady; Nariman Sepehrvand; Amir Salimi; Yousef Nademi; Kevin Bainey; Justin A. Ezekowitz; Russell Greiner; Abram Hindle; Finlay A. McAlister; Roopinder K. Sandhu; Padma Kaul (npj Digit. Medicine, 2023)

Using Bayesian Neural Networks to Select Features and Compute Credible Intervals for Personalized Survival Prediction. - Shiang Qi; Neeraj Kumar 002; Ruchika Verma; Jian-Yi Xu; Grace Shen-Tu; Russell Greiner (IEEE Trans. Biomed. Eng., 2023)

Federated Learning and Differential Privacy Techniques on Multi-hospital Population-scale Electrocardiogram Data. - Vikhyat Agrawal; Sunil Vasu Kalmady; Venkataseetharam Manoj Malipeddi; Manisimha Varma Manthena; Weijie Sun 004; Md. Saiful Islam 007; Abram Hindle; Padma Kaul; Russell Greiner (ICMHI, 2024)

Conformalized Survival Distributions: A Generic Post-Process to Increase Calibration. - Shiang Qi; Yakun Yu; Russell Greiner (ICML, 2024)

MassSpecGym: A benchmark for the discovery and identification of molecules. - Roman Bushuiev; Anton Bushuiev; Niek F. de Jonge; Adamo Young; Fleming Kretschmer; Raman Samusevich; Janne Heirman; Fei Wang 062; Luke Zhang; Kai Dührkop; Marcus Ludwig; Nils A. Haupt; et al. (NeurIPS, 2024)

Toward Conditional Distribution Calibration in Survival Prediction. - Shiang Qi; Yakun Yu; Russell Greiner (NeurIPS, 2024)

An early warning indicator trained on stochastic disease-spreading models with different noises. - Amit K. Chakraborty; Shan Gao; Reza Miry; Pouria Ramazi; Russell Greiner; Mark A. Lewis; Hao Wang 027 (CoRR, 2024)

FraGNNet: A Deep Probabilistic Model for Mass Spectrum Prediction. - Adamo Young; Fei Wang 062; David S. Wishart; Bo Wang 044; Hannes L. Röst; Russ Greiner (CoRR, 2024)

Early detection of disease outbreaks and non-outbreaks using incidence data. - Shan Gao; Amit K. Chakraborty; Russell Greiner; Mark A. Lewis; Hao Wang 027 (CoRR, 2024)

Federated Learning and Differential Privacy Techniques on Multi-hospital Population-scale Electrocardiogram Data. - Vikhyat Agrawal; Sunil Vasu Kalmady; Venkataseetharam Manoj Malipeddi; Manisimha Varma Manthena; Weijie Sun 004; Saiful Islam; Abram Hindle; Padma Kaul; Russell Greiner (CoRR, 2024)

MENSA: A Multi-Event Network for Survival Analysis under Informative Censoring. - Christian Marius Lillelund; Ali Hossein Gharari Foomani; Weijie Sun 004; Shiang Qi; Russell Greiner (CoRR, 2024)

The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue. - Philippe Weitz; Masi Valkonen; Leslie Solorzano; Circe Carr; Kimmo Kartasalo; Constance Boissin; Sonja Koivukoski; Aino Kuusela; Dusan Rasic; Yanbo Feng; Sandra Kristiane Sinius Pouplier; Abhinav Sharma; et al. (Medical Image Anal., 2024)

Development and validation of machine learning algorithms based on electrocardiograms for cardiovascular diagnoses at the population level. - Sunil Vasu Kalmady; Amir Salimi; Weijie Sun 004; Nariman Sepehrvand; Yousef Nademi; Kevin Bainey; Justin A. Ezekowitz; Abram Hindle; Finlay A. McAlister; Russell Greiner; Roopinder K. Sandhu; Padma Kaul (npj Digit. Medicine, 2024)

Extendable and Iterative Structure Learning Strategy for Bayesian Networks. - Hamid Kalantari; Russell Greiner; Pouria Ramazi (ICLR, 2025)

Methods in dynamic treatment regimens using observational healthcare data: A systematic review. - David Liang; Animesh Kumar Paul; Daniala L. Weir; Vera H. M. Deneer; Russell Greiner; Arno Siebes; Helga Gardarsdottir (Comput. Methods Programs Biomed., 2025)

Early detection of disease outbreaks and non-outbreaks using incidence data: A framework using feature-based time series classification and machine learning. - Shan Gao; Amit K. Chakraborty; Russell Greiner; Mark A. Lewis; Hao Wang 027 (PLoS Comput. Biol., 2025)

FraGNNet: A Deep Probabilistic Model for Tandem Mass Spectrum Prediction. - Adamo Young; Fei Wang 062; David S. Wishart; Bo Wang 044; Russell Greiner; Hannes Rost (Trans. Mach. Learn. Res., 2025)

Deep Learning for Disease Outbreak Prediction: A Robust Early Warning Signal for Transcritical Bifurcations. - Reza Miry; Amit K. Chakraborty; Russell Greiner; Mark A. Lewis; Hao Wang 027; Tianyu Guan; Pouria Ramazi (CoRR, 2025)

Practical Evaluation of Copula-based Survival Metrics: Beyond the Independent Censoring Assumption. - Christian Marius Lillelund; Shiqi Liu 004; Russell Greiner (CoRR, 2025)

Censoring-Aware Tree-Based Reinforcement Learning for Estimating Dynamic Treatment Regimes with Censored Outcomes. - Animesh Kumar Paul; Russell Greiner (CoRR, 2025)

Stop Chasing the C-index: This Is How We Should Evaluate Our Survival Models. - Christian Marius Lillelund; Shiang Qi; Russell Greiner; Christian Fischer Pedersen (CoRR, 2025)

A meaningful prediction of functional decline in amyotrophic lateral sclerosis based on multi-event survival analysis. - Christian Marius Lillelund; Sanjay Kalra; Russell Greiner (CoRR, 2025)