Russell Greiner

259 papers A* 56A 13B 4C 5Misc 8Journal 119Unranked 52

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Learning dynamic binary treatment policies under treatment selection bias: A Conservative Q-Learning approach with representation balancing. J. Biomed. Informatics Animesh Kumar Paul, Russell Greiner
2026	J	`jnl`	Temporally consistent survival prediction for non-uniform longitudinal data. J. Biomed. Informatics Harrison Fah, Russell Greiner, Roger A. Dixon
2025	J	`jnl`	A meaningful prediction of functional decline in amyotrophic lateral sclerosis based on multi-event survival analysis. CoRR Christian Marius Lillelund, Sanjay Kalra, Russell Greiner
2025	J	`jnl`	Budget-constrained Active Learning to Effectively De-censor Survival Data. CoRR Ali Parsaee, Bei Jiang, Zachary Friggstad, Russell Greiner
2025	J	`jnl`	Censoring-Aware Tree-Based Reinforcement Learning for Estimating Dynamic Treatment Regimes with Censored Outcomes. CoRR Animesh Kumar Paul, Russell Greiner
2025	J	`jnl`	Deep Learning for Disease Outbreak Prediction: A Robust Early Warning Signal for Transcritical Bifurcations. CoRR Reza Miry, Amit K. Chakraborty, Russell Greiner, Mark A. Lewis, Hao Wang, Tianyu Guan, Pouria Ramazi
2025	J	`jnl`	Early detection of disease outbreaks and non-outbreaks using incidence data: A framework using feature-based time series classification and machine learning. PLoS Comput. Biol. Shan Gao, Amit K. Chakraborty, Russell Greiner, Mark A. Lewis, Hao Wang
2025	A*	`conf`	Extendable and Iterative Structure Learning Strategy for Bayesian Networks. ICLR Hamid Kalantari, Russell Greiner, Pouria Ramazi
2025	J	`jnl`	FraGNNet: A Deep Probabilistic Model for Tandem Mass Spectrum Prediction. Trans. Mach. Learn. Res. Adamo Young, Fei Wang, David S. Wishart, Bo Wang, Russell Greiner, Hannes Rost
2025	J	`jnl`	Methods in dynamic treatment regimens using observational healthcare data: A systematic review. Comput. Methods Programs Biomed. David Liang, Animesh Kumar Paul, Daniala L. Weir, Vera H. M. Deneer, Russell Greiner, Arno Siebes, Helga Gardarsdottir
2025	J	`jnl`	Practical Evaluation of Copula-based Survival Metrics: Beyond the Independent Censoring Assumption. CoRR Christian Marius Lillelund, Shiqi Liu, Russell Greiner
2025	J	`jnl`	Stop Chasing the C-index: This Is How We Should Evaluate Our Survival Models. CoRR Christian Marius Lillelund, Shiang Qi, Russell Greiner, Christian Fischer Pedersen
2024	J	`jnl`	An early warning indicator trained on stochastic disease-spreading models with different noises. CoRR Amit K. Chakraborty, Shan Gao, Reza Miry, Pouria Ramazi, Russell Greiner, Mark A. Lewis, Hao Wang
2024	A*	`conf`	Conformalized Survival Distributions: A Generic Post-Process to Increase Calibration. ICML Shiang Qi, Yakun Yu, Russell Greiner
2024	J	`jnl`	Conformalized Survival Distributions: A Generic Post-Process to Increase Calibration. CoRR Shiang Qi, Yakun Yu, Russell Greiner
2024	J	`jnl`	Development and validation of machine learning algorithms based on electrocardiograms for cardiovascular diagnoses at the population level. npj Digit. Medicine Sunil Vasu Kalmady, Amir Salimi, Weijie Sun, Nariman Sepehrvand, Yousef Nademi, Kevin Bainey, Justin A. Ezekowitz, Abram Hindle, Finlay A. McAlister, Russell Greiner, Roopinder K. Sandhu, Padma Kaul
2024	J	`jnl`	Early detection of disease outbreaks and non-outbreaks using incidence data. CoRR Shan Gao, Amit K. Chakraborty, Russell Greiner, Mark A. Lewis, Hao Wang
2024	—	`conf`	Federated Learning and Differential Privacy Techniques on Multi-hospital Population-scale Electrocardiogram Data. ICMHI Vikhyat Agrawal, Sunil Vasu Kalmady, Venkataseetharam Manoj Malipeddi, Manisimha Varma Manthena, Weijie Sun, Md. Saiful Islam, Abram Hindle, Padma Kaul, Russell Greiner
2024	J	`jnl`	Federated Learning and Differential Privacy Techniques on Multi-hospital Population-scale Electrocardiogram Data. CoRR Vikhyat Agrawal, Sunil Vasu Kalmady, Venkataseetharam Manoj Malipeddi, Manisimha Varma Manthena, Weijie Sun, Saiful Islam, Abram Hindle, Padma Kaul, Russell Greiner
2024	J	`jnl`	MENSA: A Multi-Event Network for Survival Analysis under Informative Censoring. CoRR Christian Marius Lillelund, Ali Hossein Gharari Foomani, Weijie Sun, Shiang Qi, Russell Greiner
2024	A*	`conf`	MassSpecGym: A benchmark for the discovery and identification of molecules. NeurIPS Roman Bushuiev, Anton Bushuiev, Niek F. de Jonge, Adamo Young, Fleming Kretschmer, Raman Samusevich, Janne Heirman, Fei Wang, Luke Zhang, Kai Dührkop, Marcus Ludwig, Nils A. Haupt, Apurva Kalia, Corinna Brungs, Robin Schmid, Russell Greiner, Bo Wang, David S. Wishart, Liping Liu, Juho Rousu, Wout Bittremieux, Hannes Rost, Tytus D. Mak, Soha Hassoun, Florian Huber, Justin J. J. van der Hooft, Michael A. Stravs, Sebastian Böcker, Josef Sivic, Tomás Pluskal
2024	J	`jnl`	MassSpecGym: A benchmark for the discovery and identification of molecules. CoRR Roman Bushuiev, Anton Bushuiev, Niek F. de Jonge, Adamo Young, Fleming Kretschmer, Raman Samusevich, Janne Heirman, Fei Wang, Luke Zhang, Kai Dührkop, Marcus Ludwig, Nils A. Haupt, Apurva Kalia, Corinna Brungs, Robin Schmid, Russell Greiner, Bo Wang, David S. Wishart, Li-Ping Liu, Juho Rousu, Wout Bittremieux, Hannes Rost, Tytus D. Mak, Soha Hassoun, Florian Huber, Justin J. J. van der Hooft, Michael A. Stravs, Sebastian Böcker, Josef Sivic, Tomás Pluskal
2024	J	`jnl`	The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue. Medical Image Anal. 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, Kajsa Ledesma Eriksson, Stephanie Robertson, Christian Marzahl, Chandler D. Gatenbee, Alexander R. A. Anderson, Marek Wodzinski, Artur Jurgas, Niccolò Marini, Manfredo Atzori, Henning Müller, Daniel Budelmann, Nick Weiss, Stefan Heldmann, Johannes Lotz, Jelmer M. Wolterink, Bruno De Santi, Abhijeet Patil, Amit Sethi, Satoshi Kondo, Satoshi Kasai, Kousuke Hirasawa, Mahtab Farrokh, Neeraj Kumar, Russell Greiner, Leena Latonen, Anne-Vibeke Laenkholm, Johan Hartman, Pekka Ruusuvuori, Mattias Rantalainen
2024	A*	`conf`	Toward Conditional Distribution Calibration in Survival Prediction. NeurIPS Shiang Qi, Yakun Yu, Russell Greiner
2024	J	`jnl`	Toward Conditional Distribution Calibration in Survival Prediction. CoRR Shiang Qi, Yakun Yu, Russell Greiner
2023	A*	`conf`	An Effective Meaningful Way to Evaluate Survival Models. ICML Shiang Qi, Neeraj Kumar, Mahtab Farrokh, Weijie Sun, Li-Hao Kuan, Rajesh Ranganath, Ricardo Henao, Russell Greiner
2023	J	`jnl`	An Effective Meaningful Way to Evaluate Survival Models. CoRR Shiang Qi, Neeraj Kumar, Mahtab Farrokh, Weijie Sun, Li-Hao Kuan, Rajesh Ranganath, Ricardo Henao, Russell Greiner
2023	J	`jnl`	Copula-Based Deep Survival Models for Dependent Censoring. CoRR Ali Hossein Gharari Foomani, Michael Cooper, Russell Greiner, Rahul G. Krishnan
2023	A	`conf`	Copula-based deep survival models for dependent censoring. UAI Ali Hossein Gharari Foomani, Michael Cooper, Russell Greiner, Rahul G. Krishnan
2023	Misc	`conf`	Exploring Language-Agnostic Speech Representations Using Domain Knowledge for Detecting Alzheimer's Dementia. ICASSP Zehra Shah, Shiang Qi, Fei Wang, Mahtab Farrokh, Mashrura Tasnim, Eleni Stroulia, Russell Greiner, Manos Plitsis, Athanasios Katsamanis
2023	—	`conf`	Generative Data by β-Variational Autoencoders Help Build Stronger Classifiers: ECG Use Case. SIPAIM Yousef Nademi, Sunil Vasu Kalmady, Weijie Sun, Amir Salimi, Abram Hindle, Padma Kaul, Russell Greiner
2023	J	`jnl`	Modeling and Forecasting COVID-19 Cases using Latent Subpopulations. CoRR Roberto Vega, Zehra Shah, Pouria Ramazi, Russell Greiner
2023	—	`conf`	Supervised Electrocardiogram(ECG) Features Outperform Knowledge-based And Unsupervised Features In Individualized Survival Prediction. ML4H@NeurIPS Yousef Nademi, Sunil Vasu Kalmady, Weijie Sun, Shiang Qi, Abram Hindle, Padma Kaul, Russell Greiner
2023	J	`jnl`	The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue. CoRR 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, Kajsa Ledesma Eriksson, Stephanie Robertson, Christian Marzahl, Chandler D. Gatenbee, Alexander R. A. Anderson, Marek Wodzinski, Artur Jurgas, Niccolò Marini, Manfredo Atzori, Henning Müller, Daniel Budelmann, Nick Weiss, Stefan Heldmann, Johannes Lotz, Jelmer M. Wolterink, Bruno De Santi, Abhijeet Patil, Amit Sethi, Satoshi Kondo, Satoshi Kasai, Kousuke Hirasawa, Mahtab Farrokh, Neeraj Kumar, Russell Greiner, Leena Latonen, Anne-Vibeke Laenkholm, Johan Hartman, Pekka Ruusuvuori, Mattias Rantalainen
2023	J	`jnl`	Towards artificial intelligence-based learning health system for population-level mortality prediction using electrocardiograms. npj Digit. Medicine Weijie Sun, 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
2023	J	`jnl`	Using Bayesian Neural Networks to Select Features and Compute Credible Intervals for Personalized Survival Prediction. IEEE Trans. Biomed. Eng. Shiang Qi, Neeraj Kumar, Ruchika Verma, Jian-Yi Xu, Grace Shen-Tu, Russell Greiner
2022	J	`jnl`	BioTransformer 3.0 - a web server for accurately predicting metabolic transformation products. Nucleic Acids Res. David S. Wishart, Siyang Tian, Dana Allen, Eponine Oler, Harrison Peters, Vicki W. Lui, Vasuk Gautam, Yannick Djoumbou Feunang, Russell Greiner, Thomas O. Metz
2022	J	`jnl`	CFM-ID 4.0 - a web server for accurate MS-based metabolite identification. Nucleic Acids Res. Fei Wang, Dana Allen, Siyang Tian, Eponine Oler, Vasuk Gautam, Russell Greiner, Thomas O. Metz, David S. Wishart
2022	J	`jnl`	Domain-shift adaptation via linear transformations. CoRR Roberto Vega, Russell Greiner
2022	J	`jnl`	ECG for high-throughput screening of multiple diseases: Proof-of-concept using multi-diagnosis deep learning from population-based datasets. CoRR Weijie Sun, Sunil Vasu Kalmady, Amir Salimi, Nariman Sepehrvand, Eric Ly, Abram Hindle, Russell Greiner, Padma Kaul
2022	J	`jnl`	Editorial: Multi-site neuroimage analysis: Domain adaptation and batch effects. Frontiers Neuroinformatics Muhammad Yousefnezhad, Daoqiang Zhang, Andrew J. Greenshaw, Russell Greiner
2022	J	`jnl`	HMDB 5.0: the Human Metabolome Database for 2022. Nucleic Acids Res. David S. Wishart, Anchi Guo, Eponine Oler, Fei Wang, Afia Anjum, Harrison Peters, Raynard Dizon, Zinat Sayeeda, Siyang Tian, Brian L. Lee, Mark V. Berjanskii, Robert Mah, Mai Yamamoto, Juan Jovel, Claudia Torres-Calzada, Mickel Hiebert-Giesbrecht, Vicki W. Lui, Dorna Varshavi, Dorsa Varshavi, Dana Allen, David Arndt, Nitya Khetarpal, Aadhavya Sivakumaran, Karxena Harford, Selena Sanford, Kristen Yee, Xuan Cao, Zachary Budinski, Jaanus Liigand, Lun Zhang, Jiamin Zheng, Rupasri Mandal, Naama Karu, Maija Dambrova, Helgi B. Schiöth, Russell Greiner, Vasuk Gautam
2022	J	`jnl`	Improving ECG-based COVID-19 diagnosis and mortality predictions using pre-pandemic medical records at population-scale. CoRR Weijie Sun, Sunil Vasu Kalmady, Nariman Sepehrvand, Luan Manh Chu, Zihan Wang, Amir Salimi, Abram Hindle, Russell Greiner, Padma Kaul
2022	J	`jnl`	Multi-Source Domain Adaptation Techniques for Mitigating Batch Effects: A Comparative Study. Frontiers Neuroinformatics Rohan Panda, Sunil Vasu Kalmady, Russell Greiner
2021	J	`jnl`	A deep generative model enables automated structure elucidation of novel psychoactive substances. Nat. Mach. Intell. Michael A. Skinnider, Fei Wang, Daniel Pasin, Russell Greiner, Leonard J. Foster, Petur W. Dalsgaard, David S. Wishart
2021	J	`jnl`	CyProduct: A Software Tool for Accurately Predicting the Byproducts of Human Cytochrome P450 Metabolism. J. Chem. Inf. Model. Siyang Tian, Xuan Cao, Russell Greiner, Carin Li, Anchi Guo, David S. Wishart
2021	—	`conf`	Finding Relevant Features for Different Times in Survival Prediction by Discrete Hazard Bayesian Network. SPACA Li-Hao Kuan, Russell Greiner
2021	J	`jnl`	Identification of spectral features in the longwave infrared (LWIR) spectra of leaves for the discrimination of tropical dry forest tree species. Int. J. Appl. Earth Obs. Geoinformation Yaqian Long, Benoit Rivard, Arturo Sanchez-Azofeifa, Russell Greiner, Dominica E. Harrison, Sen Jia
2021	J	`jnl`	Learning Language and Acoustic Models for Identifying Alzheimer's Dementia From Speech. Frontiers Comput. Sci. Zehra Shah, Jeffrey Sawalha, Mashrura Tasnim, Shiang Qi, Eleni Stroulia, Russell Greiner
2021	—	`conf`	Preface: AAAI Spring Symposium on Survival Prediction - Algorithms, Challenges, and Applications 2021. SPACA Russell Greiner, Neeraj Kumar, Thomas Alexander Gerds, Mihaela van der Schaar
2021	—	`ed.`	Proceedings of AAAI Symposium on Survival Prediction - Algorithms, Challenges and Applications, SPACA 2021, Stanford University, Palo Alto, CA, USA, March 22-24, 2021. SPACA Russell Greiner, Neeraj Kumar, Thomas Alexander Gerds, Mihaela van der Schaar
2021	J	`jnl`	SIMLR: Machine Learning inside the SIR model for COVID-19 Forecasting. CoRR Roberto Vega, Leonardo Flores, Russell Greiner
2021	J	`jnl`	Sample Efficient Learning of Image-Based Diagnostic Classifiers Using Probabilistic Labels. CoRR Roberto Vega, Pouneh Gorji, Zichen Zhang, Xuebin Qin, Abhilash Rakkunedeth Hareendranathan, Jeevesh Kapur, Jacob L. Jaremko, Russell Greiner
2021	A	`conf`	Sample efficient learning of image-based diagnostic classifiers via probabilistic labels. AISTATS Roberto Vega, Pouneh Gorji, Zichen Zhang, Xuebin Qin, Abhilash Rakkunedeth Hareendranathan, Jeevesh Kapur, Jacob L. Jaremko, Russell Greiner
2021	J	`jnl`	The challenge of predicting blood glucose concentration changes in patients with type I diabetes. Health Informatics J. Neil C. Borle, Edmond A. Ryan, Russell Greiner
2021	J	`jnl`	Variational Auto-Encoder Architectures that Excel at Causal Inference. CoRR Negar Hassanpour, Russell Greiner
2020	A*	`conf`	Domain Aggregation Networks for Multi-Source Domain Adaptation. ICML Junfeng Wen, Russell Greiner, Dale Schuurmans
2020	J	`jnl`	Effective Ways to Build and Evaluate Individual Survival Distributions. J. Mach. Learn. Res. Humza Haider, Bret Hoehn, Sarah Davis, Russell Greiner
2020	A*	`conf`	Learning Disentangled Representations for CounterFactual Regression. ICLR Negar Hassanpour, Russell Greiner
2020	A*	`conf`	Shared Space Transfer Learning for analyzing multi-site fMRI data. NeurIPS Muhammad Yousefnezhad, Alessandro Selvitella, Daoqiang Zhang, Andrew J. Greenshaw, Russell Greiner
2020	J	`jnl`	Shared Space Transfer Learning for analyzing multi-site fMRI data. CoRR Muhammad Yousefnezhad, Alessandro Selvitella, Daoqiang Zhang, Andrew J. Greenshaw, Russell Greiner
2019	J	`jnl`	A simple classification framework for predicting Alzheimer's disease from region-based grey matter volume and APOE genotype status. Artif. Intell. Res. Reyhaneh Ghoreishiamiri, Graham Little, Matthew R. G. Brown, Russell Greiner
2019	J	`jnl`	BioTransformer: a comprehensive computational tool for small molecule metabolism prediction and metabolite identification. J. Cheminformatics Yannick Djoumbou Feunang, Jarlei Fiamoncini, Alberto Gil-de-la-Fuente, Russell Greiner, Claudine Manach, David S. Wishart
2019	A*	`conf`	CounterFactual Regression with Importance Sampling Weights. IJCAI Negar Hassanpour, Russell Greiner
2019	J	`jnl`	Domain Aggregation Networks for Multi-Source Domain Adaptation. CoRR Junfeng Wen, Russell Greiner, Dale Schuurmans
2019	J	`jnl`	Gene Expression based Survival Prediction for Cancer Patients: A Topic Modeling Approach. CoRR Luke N. Kumar, Russell Greiner
2019	C	`conf`	Ischemic Stroke Lesion Prediction in CT Perfusion Scans Using Multiple Parallel U-Nets Following by a Pixel-Level Classifier. BIBE Mohsen Soltanpour, Russell Greiner, Pierre Boulanger, Brian Buck
2019	A*	`conf`	Learning Macroscopic Brain Connectomes via Group-Sparse Factorization. NeurIPS Farzane Aminmansour, Andrew Patterson, Lei Le, Yisu Peng, Daniel Mitchell, Franco Pestilli, Cesar F. Caiafa, Russell Greiner, Martha White
2019	J	`jnl`	Low-Dimensional Perturb-and-MAP Approach for Learning Restricted Boltzmann Machines. Neural Process. Lett. Jakub M. Tomczak, Szymon Zareba, Siamak Ravanbakhsh, Russell Greiner
2019	J	`jnl`	Reducing Selection Bias in Counterfactual Reasoning for Individual Treatment Effects Estimation. CoRR Zichen Zhang, Qingfeng Lan, Lei Ding, Yue Wang, Negar Hassanpour, Russell Greiner
2019	A*	`conf`	Simultaneous Prediction Intervals for Patient-Specific Survival Curves. IJCAI Samuel Sokota, Ryan D'Orazio, Khurram Javed, Humza Haider, Russell Greiner
2019	J	`jnl`	Simultaneous Prediction Intervals for Patient-Specific Survival Curves. CoRR Samuel Sokota, Ryan D'Orazio, Khurram Javed, Humza Haider, Russell Greiner
2019	J	`jnl`	The Challenge of Predicting Meal-to-meal Blood Glucose Concentrations for Patients with Type I Diabetes. CoRR Neil C. Borle, Edmond A. Ryan, Russell Greiner
2018	—	`conf`	A Novel Evaluation Methodology for Assessing Off-Policy Learning Methods in Contextual Bandits. Canadian AI Negar Hassanpour, Russell Greiner
2018	A*	`conf`	Analyzing the effects of test driven development in GitHub. ICSE Neil C. Borle, Meysam Feghhi, Eleni Stroulia, Russell Greiner, Abram Hindle
2018	J	`jnl`	Analyzing the effects of test driven development in GitHub. Empir. Softw. Eng. Neil C. Borle, Meysam Feghhi, Eleni Stroulia, Russell Greiner, Abram Hindle
2018	J	`jnl`	CypReact: A Software Tool for in Silico Reactant Prediction for Human Cytochrome P450 Enzymes. J. Chem. Inf. Model. Siyang Tian, Yannick Djoumbou Feunang, Russell Greiner, David S. Wishart
2018	J	`jnl`	Effective Ways to Build and Evaluate Individual Survival Distributions. CoRR Humza Haider, Bret Hoehn, Sarah Davis, Russell Greiner
2018	—	`conf`	Finding Effective Ways to (Machine) Learn fMRI-Based Classifiers from Multi-site Data. MLCN/DLF/iMIMIC@MICCAI Roberto Vega, Russell Greiner
2017	J	`jnl`	Assessment of feature selection and classification methods for recognizing motor imagery tasks from electroencephalographic signals. Artif. Intell. Res. Roberto Vega, Touqir Sajed, Kory Wallace Mathewson, Kriti Khare, Patrick M. Pilarski, Russell Greiner, Gildardo Sánchez-Ante, Javier Mauricio Antelis
2017	A	`conf`	Deep Green: Modelling Time-Series of Software Energy Consumption. ICSME Stephen Romansky, Neil C. Borle, Shaiful Alam Chowdhury, Abram Hindle, Russell Greiner
2017	J	`jnl`	Detecting duplicate bug reports with software engineering domain knowledge. J. Softw. Evol. Process. Karan Aggarwal, Finbarr Timbers, Tanner Rutgers, Abram Hindle, Eleni Stroulia, Russell Greiner
2017	J	`jnl`	Learning Neural Markers of Schizophrenia Disorder Using Recurrent Neural Networks. CoRR Jumana Dakka, Pouya Bashivan, Mina Gheiratmand, Irina Rish, Shantenu Jha, Russell Greiner
2017	—	`conf`	Learning discriminative functional network features of schizophrenia. Biomedical Applications in Molecular, Structural, and Functional Imaging Mina Gheiratmand, Irina Rish, Guillermo A. Cecchi, Matthew R. G. Brown, Russell Greiner, Pouya Bashivan, Pablo Polosecki, Serdar M. Dursun
2016	A*	`conf`	Boolean Matrix Factorization and Noisy Completion via Message Passing. ICML Siamak Ravanbakhsh, Barnabás Póczos, Russell Greiner
2016	J	`jnl`	ClassyFire: automated chemical classification with a comprehensive, computable taxonomy. J. Cheminformatics 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
2016	A	`conf`	Stochastic Neural Networks with Monotonic Activation Functions. AISTATS Siamak Ravanbakhsh, Barnabás Póczos, Jeff G. Schneider, Dale Schuurmans, Russell Greiner
2016	J	`jnl`	Stochastic Neural Networks with Monotonic Activation Functions. CoRR Siamak Ravanbakhsh, Barnabás Póczos, Jeff G. Schneider, Dale Schuurmans, Russell Greiner
2015	—	`conf`	A system-call based model of software energy consumption without hardware instrumentation. IGSC Shaiful Alam Chowdhury, Luke N. Kumar, Md. Toukir Imam, Mohomed Shazan Mohomed Jabbar, Varun Sapra, Karan Aggarwal, Abram Hindle, Russell Greiner
2015	J	`jnl`	Boolean Matrix Factorization and Completion via Message Passing. CoRR Siamak Ravanbakhsh, Russell Greiner
2015	A*	`conf`	Correcting Covariate Shift with the Frank-Wolfe Algorithm. IJCAI Junfeng Wen, Russell Greiner, Dale Schuurmans
2015	A	`conf`	Detecting duplicate bug reports with software engineering domain knowledge. SANER Karan Aggarwal, Tanner Rutgers, Finbarr Timbers, Abram Hindle, Russell Greiner, Eleni Stroulia
2015	J	`jnl`	Perturbed message passing for constraint satisfaction problems. J. Mach. Learn. Res. Siamak Ravanbakhsh, Russell Greiner
2014	B	`conf`	A robust convergence index filter for breast cancer cell segmentation. ICIP Baidya Nath Saha, Amritpal Saini, Nilanjan Ray, Russell Greiner, Judith Hugh, Mauro Tambasco
2014	J	`jnl`	Accurate, fully-automated NMR spectral profiling for metabolomics. CoRR Siamak Ravanbakhsh, Philip Liu, Trent C. Bjorndahl, Rupasri Mandal, Jason R. Grant, Michael Wilson, Roman Eisner, Igor Sinelnikov, Xiaoyu Hu, Claudio Luchinat, Russell Greiner, David S. Wishart
2014	J	`jnl`	Algebra of inference in graphical models revisited. CoRR Siamak Ravanbakhsh, Russell Greiner
2014	—	`conf`	Augmentative Message Passing for Traveling Salesman Problem and Graph Partitioning. NIPS Siamak Ravanbakhsh, Reihaneh Rabbany, Russell Greiner
2014	J	`jnl`	Augmentative Message Passing for Traveling Salesman Problem and Graph Partitioning. CoRR Siamak Ravanbakhsh, Reihaneh Rabbany, Russell Greiner
2014	—	`conf`	Budgeted transcript discovery: A framework for joint exploration and validation studies. BIBM Sheehan Khan, Russell Greiner
2014	J	`jnl`	CFM-ID: a web server for annotation, spectrum prediction and metabolite identification from tandem mass spectra. Nucleic Acids Res. Felicity Allen, Allison Pon, Michael Wilson, Russell Greiner, David S. Wishart
2014	A*	`conf`	Min-Max Problems on Factor Graphs. ICML Siamak Ravanbakhsh, Christopher Srinivasa, Brendan J. Frey, Russell Greiner
2014	J	`jnl`	Perturbed Message Passing for Constraint Satisfaction Problems. CoRR Siamak Ravanbakhsh, Russell Greiner
2014	A*	`conf`	Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification. ICML Junfeng Wen, Chun-Nam Yu, Russell Greiner
2014	—	`conf`	The Budgeted Biomarker Discovery Problem: A Variant of Association Studies. AAAI Workshop: Modern Artificial Intelligence for Health Analytics Sheehan Khan, Russell Greiner
2014	J	`jnl`	Training Restricted Boltzmann Machine by Perturbation. CoRR Siamak Ravanbakhsh, Russell Greiner, Brendan J. Frey
2013	—	`conf`	An automatic brain tumor segmentation tool. EMBC Idanis Diaz, Pierre Boulanger, Russell Greiner, Bret Hoehn, Lindsay Rowe, Albert Murtha
2013	J	`jnl`	Bayesian Error-Bars for Belief Net Inference CoRR Tim Van Allen, Russell Greiner, Peter Hooper
2013	J	`jnl`	Breast cancer prediction using genome wide single nucleotide polymorphism data. BMC Bioinform. Mohsen Hajiloo, Babak Damavandi, Metanat HooshSadat, Farzad Sangi, John R. Mackey, Carol E. Cass, Russell Greiner, Sambasivarao Damaraju
2013	J	`jnl`	Comparing Bayesian Network Classifiers CoRR Jie Cheng, Russell Greiner
2013	J	`jnl`	Competitive Fragmentation Modeling of ESI-MS/MS spectra for metabolite identification. CoRR Felicity Allen, Russell Greiner, David S. Wishart
2013	J	`jnl`	Consistency and Generalization Bounds for Maximum Entropy Density Estimation. Entropy Shaojun Wang, Russell Greiner, Shaomin Wang
2013	J	`jnl`	ETHNOPRED: a novel machine learning method for accurate continental and sub-continental ancestry identification and population stratification correction. BMC Bioinform. Mohsen Hajiloo, Yadav Sapkota, John R. Mackey, Paula Robson, Russell Greiner, Sambasivarao Damaraju
2013	J	`jnl`	Exploiting Syntactic, Semantic, and Lexical Regularities in Language Modeling via Directed Markov Random Fields. Comput. Intell. Shaojun Wang, Shaomin Wang, Li Cheng, Russell Greiner, Dale Schuurmans
2013	—	`conf`	Finding Discriminatory Genes: A Methodology for Validating Microarray Studies. ICDM Workshops Sheehan Khan, Russell Greiner
2013	—	`conf`	Fully Automated Brain Tumor Segmentation Using Two MRI Modalities. ISVC (1) Mohamed Ben Salah, Idanis Diaz, Russell Greiner, Pierre Boulanger, Bret Hoehn, Albert Murtha
2013	J	`jnl`	HMDB 3.0 - The Human Metabolome Database in 2013. Nucleic Acids Res. David S. Wishart, Timothy Jewison, Anchi Guo, Michael Wilson, Craig Knox, Yifeng Liu, Yannick Djoumbou, Rupasri Mandal, Farid Aziat, Edison Dong, Souhaila Bouatra, Igor Sinelnikov, David Arndt, Jianguo Xia, Philip Liu, Faizath Yallou, Trent C. Bjorndahl, Rolando Perez-Pineiro, Roman Eisner, Felicity Allen, Vanessa Neveu, Russell Greiner, Augustin Scalbert
2013	J	`jnl`	Learning Bayesian Nets that Perform Well CoRR Russell Greiner, Adam J. Grove, Dale Schuurmans
2013	—	`conf`	Online Learning with Costly Features and Labels. NIPS Navid Zolghadr, Gábor Bartók, Russell Greiner, András György, Csaba Szepesvári
2013	—	`conf`	Predicting Army Combat Outcomes in StarCraft. AIIDE Marius Stanescu, Sergio Poo Hernandez, Graham Erickson, Russell Greiner, Michael Buro
2012	J	`jnl`	A Generalized Loop Correction Method for Approximate Inference in Graphical Models CoRR Siamak Ravanbakhsh, Chun-Nam Yu, Russell Greiner
2012	A*	`conf`	A Generalized Loop Correction Method for Approximate Inference in Graphical Models. ICML Siamak Ravanbakhsh, Chun-Nam Yu, Russell Greiner
2012	J	`jnl`	Active Model Selection CoRR Omid Madani, Daniel J. Lizotte, Russell Greiner
2012	J	`jnl`	An experimental methodology for response surface optimization methods. J. Glob. Optim. Daniel J. Lizotte, Russell Greiner, Dale Schuurmans
2012	J	`jnl`	Budgeted Learning of Naive-Bayes Classifiers CoRR Daniel J. Lizotte, Omid Madani, Russell Greiner
2012	J	`jnl`	Combining gene expression and interaction network data to improve kidney lesion score prediction. Int. J. Bioinform. Res. Appl. Davoud Moulavi, Mohsen Hajiloo, Jörg Sander, Philip F. Halloran, Russell Greiner
2012	J	`jnl`	Improved Mean and Variance Approximations for Belief Net Responses via Network Doubling CoRR Peter Hooper, Yasin Abbasi-Yadkori, Russell Greiner, Bret Hoehn
2012	J	`jnl`	Learning to predict ice accretion on electric power lines. Eng. Appl. Artif. Intell. Ashkan Zarnani, Petr Musílek, Xiaoyu Shi, Xiaodi Ke, Hua He, Russell Greiner
2012	J	`jnl`	Quick detection of brain tumors and edemas: A bounding box method using symmetry. Comput. Medical Imaging Graph. Baidya Nath Saha, Nilanjan Ray, Russell Greiner, Albert Murtha, Hong Zhang
2012	J	`jnl`	Speeding Up Planning in Markov Decision Processes via Automatically Constructed Abstractions CoRR Alejandro Isaza, Csaba Szepesvári, Vadim Bulitko, Russell Greiner
2011	—	`conf`	A critical review of the effects of de-noising algorithms on MRI brain tumor segmentation. EMBC Idanis Diaz, Pierre Boulanger, Russell Greiner, Albert Murtha
2011	—	`conf`	Learning Patient-Specific Cancer Survival Distributions as a Sequence of Dependent Regressors. NIPS Chun-Nam Yu, Russell Greiner, Hsiu-Chin Lin, Vickie Baracos
2011	—	`conf`	Using Classifier-Based Nominal Imputation to Improve Machine Learning. PAKDD (1) Xiaoyuan Su, Russell Greiner, Taghi M. Khoshgoftaar, Amri Napolitano
2010	A*	`conf`	A Cross-Entropy Method that Optimizes Partially Decomposable Problems: A New Way to Interpret NMR Spectra. AAAI Siamak (Moshen) Ravanbakhsh, Barnabás Póczos, Russell Greiner
2010	A*	`conf`	Budgeted Distribution Learning of Belief Net Parameters. ICML Liuyang Li, Barnabás Póczos, Csaba Szepesvári, Russell Greiner
2010	J	`jnl`	Mind change optimal learning of Bayes net structure from dependency and independency data. Inf. Comput. Oliver Schulte, Wei Luo, Russell Greiner
2010	—	`conf`	The IMAP Hybrid Method for Learning Gaussian Bayes Nets. Canadian AI Oliver Schulte, Gustavo Frigo, Russell Greiner, Hassan Khosravi
2009	C	`conf`	A new hybrid method for Bayesian network learning With dependency constraints. CIDM Oliver Schulte, Gustavo Frigo, Russell Greiner, Wei Luo, Hassan Khosravi
2009	J	`jnl`	HMDB: a knowledgebase for the human metabolome. Nucleic Acids Res. 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, Jianguo Xia, Leslie Jia, Joseph A. Cruz, Emilia Lim, Constance A. Sobsey, Savita Shrivastava, Paul Huang, Philip Liu, Lydia Fang, Jun Peng, Ryan Fradette, Dean Cheng, Dan Tzur, Melisa Clements, Avalyn Lewis, Andrea De Souza, Azaret Zuniga, Margot Dawe, Yeping Xiong, Derrick Clive, Russell Greiner, Alsu Nazyrova, Rustem Shaykhutdinov, Liang Li, Hans J. Vogel, Ian J. Forsythe
2009	A	`conf`	Improved Mean and Variance Approximations for Belief Net Responses via Network Doubling. UAI Peter Hooper, Yasin Abbasi-Yadkori, Russell Greiner, Bret Hoehn
2009	—	`conf`	LILAC - Learn from Internet: Log, Annotation, and Content. AAAI Spring Symposium: Experimental Design for Real-World Systems Tingshao Zhu, Russell Greiner, Bin Hu
2009	A*	`conf`	Learning to segment from a few well-selected training images. ICML Alireza Farhangfar, Russell Greiner, Csaba Szepesvári
2009	A*	`conf`	Learning when to stop thinking and do something! ICML Barnabás Póczos, Yasin Abbasi-Yadkori, Csaba Szepesvári, Russell Greiner, Nathan R. Sturtevant
2009	J	`jnl`	Making an accurate classifier ensemble by voting on classifications from imputed learning sets. Int. J. Inf. Decis. Sci. Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greiner
2009	J	`jnl`	Predicting homologous signaling pathways using machine learning. Bioinform. Babak Bostan, Russell Greiner, Duane Szafron, Paul Lu
2009	B	`conf`	Segmentation of Lung Tumours in Positron Emission Tomography Scans: A Machine Learning Approach. AIME Aliaksei Kerhet, Cormac Small, Harvey Quon, Terence Riauka, Russell Greiner, Alexander McEwan, Wilson Roa
2009	Misc	`conf`	VipBoost: A More Accurate Boosting Algorithm. FLAIRS Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greiner
2008	—	`conf`	A Cover-Based Approach to Multi-Agent Moving Target Pursuit. AIIDE Alejandro Isaza, Jieshan Lu, Vadim Bulitko, Russell Greiner
2008	Misc	`conf`	A Fast Way to Produce Optimal Fixed-Depth Decision Trees. ISAIM Alireza Farhangfar, Russell Greiner, Martin Zinkevich
2008	Misc	`conf`	A Mixture Imputation-Boosted Collaborative Filter. FLAIRS Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greiner
2008	J	`jnl`	Clustering high dimensional data: A graph-based relaxed optimization approach. Inf. Sci. Chi-Hoon Lee, Osmar R. Zaïane, Ho-Hyun Park, Jiayuan Huang, Russell Greiner
2008	A*	`conf`	Constrained Classification on Structured Data. AAAI Chi-Hoon Lee, Matthew R. G. Brown, Russell Greiner, Shaojun Wang, Albert Murtha
2008	C	`conf`	Does Wikipedia Information Help Netflix Predictions? ICMLA John D. Lees-Miller, Fraser Anderson, Bret Hoehn, Russell Greiner
2008	J	`jnl`	Heterogeneous Stacking for Classification-Driven Watershed Segmentation. EURASIP J. Adv. Signal Process. Ilya Levner, Hong Zhang, Russell Greiner
2008	J	`jnl`	Improving subcellular localization prediction using text classification and the gene ontology. Bioinform. Alona Fyshe, Yifeng Liu, Duane Szafron, Russell Greiner, Paul Lu
2008	Misc	`conf`	Imputation-boosted collaborative filtering using machine learning classifiers. SAC Xiaoyuan Su, Taghi M. Khoshgoftaar, Xingquan Zhu, Russell Greiner
2008	—	`conf`	Imputed Neighborhood Based Collaborative Filtering. Web Intelligence Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greiner
2008	J	`jnl`	Quantifying the uncertainty of a belief net response: Bayesian error-bars for belief net inference. Artif. Intell. Tim Van Allen, Ajit Singh, Russell Greiner, Peter Hooper
2008	—	`conf`	Segmenting Brain Tumors Using Pseudo-Conditional Random Fields. MICCAI (1) Chi-Hoon Lee, Shaojun Wang, Albert Murtha, Matthew R. G. Brown, Russell Greiner
2008	A	`conf`	Speeding Up Planning in Markov Decision Processes via Automatically Constructed Abstraction. UAI Alejandro Isaza, Csaba Szepesvári, Vadim Bulitko, Russell Greiner
2008	B	`conf`	Supervised image segmentation via ground truth decomposition. ICIP Ilya Levner, Russell Greiner, Hong Zhang
2008	—	`conf`	Using Imputation Techniques to Help Learn Accurate Classifiers. ICTAI (1) Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greiner
2007	J	`jnl`	Focus of Attention in Reinforcement Learning. J. Univers. Comput. Sci. Lihong Li, Vadim Bulitko, Russell Greiner
2007	J	`jnl`	HMDB: the Human Metabolome Database. Nucleic Acids Res. 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, Mike Lewis, Marie-Aude Coutouly, Ian J. Forsythe, Peter Tang, Savita Shrivastava, Kevin Jeroncic, Paul Stothard, Godwin Amegbey, David Block, David D. Hau, James Wagner, Jessica Miniaci, Melisa Clements, Mulu Gebremedhin, Natalie Guo, Ying Zhang, Gavin E. Duggan, Glen D. MacInnis, Alim M. Weljie, Reza Dowlatabadi, Fiona Bamforth, Derrick Clive, Russell Greiner, Liang Li, Tom Marrie, Brian D. Sykes, Hans J. Vogel, Lori Querengesser
2007	—	`conf`	Hybrid Collaborative Filtering Algorithms Using a Mixture of Experts. Web Intelligence Xiaoyuan Su, Russell Greiner, Taghi M. Khoshgoftaar, Xingquan Zhu
2007	A*	`conf`	Mind Change Optimal Learning of Bayes Net Structure. COLT Oliver Schulte, Wei Luo, Russell Greiner
2007	A*	`conf`	Optimistic Active-Learning Using Mutual Information. IJCAI Yuhong Guo, Russell Greiner
2007	Misc	`conf`	Session Introduction. Pacific Symposium on Biocomputing David S. Wishart, Russell Greiner
2006	—	`conf`	A Classification-Based Glioma Diffusion Model Using MRI Data. Canadian AI Marianne Morris, Russell Greiner, Jörg Sander, Albert Murtha, Mark Schmidt
2006	A	`conf`	Automatic construction of personalized customer interfaces. IUI Robert Price, Russell Greiner, Gerald Häubl, Alden Flatt
2006	—	`conf`	Efficient Spatial Classification Using Decoupled Conditional Random Fields. PKDD Chi-Hoon Lee, Russell Greiner, Osmar R. Zaïane
2006	J	`jnl`	Finding optimal satisficing strategies for and-or trees. Artif. Intell. Russell Greiner, Ryan Hayward, Magdalena Jankowska, Michael Molloy
2006	—	`conf`	Information Marginalization on Subgraphs. PKDD Jiayuan Huang, Tingshao Zhu, Russell Greiner, Dengyong Zhou, Dale Schuurmans
2006	—	`conf`	Learning Policies for Efficiently Identifying Objects of Many Classes. ICPR (3) Ramana Isukapalli, Ahmed M. Elgammal, Russell Greiner
2006	J	`jnl`	Learning a Classification-based Glioma Growth Model Using MRI Data. J. Comput. Marianne Morris, Russell Greiner, Jörg Sander, Albert Murtha, Mark Schmidt
2006	—	`conf`	Learning to Detect Objects of Many Classes Using Binary Classifiers. ECCV (1) Ramana Isukapalli, Ahmed M. Elgammal, Russell Greiner
2006	—	`conf`	Learning to Identify Facial Expression During Detection Using Markov Decision Process. FGR Ramana Isukapalli, Ahmed M. Elgammal, Russell Greiner
2006	—	`conf`	Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields. NIPS Chi-Hoon Lee, Shaojun Wang, Feng Jiao, Dale Schuurmans, Russell Greiner
2006	A*	`conf`	Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling. ACL Feng Jiao, Shaojun Wang, Chi-Hoon Lee, Russell Greiner, Dale Schuurmans
2006	—	`conf`	Stochastic Analysis of Lexical and Semantic Enhanced Structural Language Model. ICGI Shaojun Wang, Shaomin Wang, Li Cheng, Russell Greiner, Dale Schuurmans
2006	J	`jnl`	The Path-A metabolic pathway prediction web server. Nucleic Acids Res. Luca Pireddu, Duane Szafron, Paul Lu, Russell Greiner
2006	A*	`conf`	Using query-specific variance estimates to combine Bayesian classifiers. ICML Chi-Hoon Lee, Russell Greiner, Shaojun Wang
2006	A*	`conf`	Visual Explanation of Evidence with Additive Classifiers. AAAI Brett Poulin, Roman Eisner, Duane Szafron, Paul Lu, Russell Greiner, David S. Wishart, Alona Fyshe, Brandon Pearcy, Cam Macdonell, John Anvik
2005	J	`jnl`	BASys: a web server for automated bacterial genome annotation. Nucleic Acids Res. Gary H. Van Domselaar, Paul Stothard, Savita Shrivastava, Joseph A. Cruz, Anchi Guo, Xiaoli Dong, Paul Lu, Duane Szafron, Russell Greiner, David S. Wishart
2005	A*	`conf`	Discriminative Model Selection for Belief Net Structures. AAAI Yuhong Guo, Russell Greiner
2005	A*	`conf`	Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields. ICML Shaojun Wang, Shaomin Wang, Russell Greiner, Dale Schuurmans, Li Cheng
2005	A*	`conf`	Goal-Directed Site-Independent Recommendations from Passive Observations. AAAI Tingshao Zhu, Russell Greiner, Gerald Häubl, Kevin Jewell, Robert Price
2005	C	`conf`	Improving Protein Function Prediction Using the Hierarchical Structure of the Gene Ontology. CIBCB Roman Eisner, Brett Poulin, Duane Szafron, Paul Lu, Russell Greiner
2005	A*	`conf`	Learning Coordination Classifiers. IJCAI Yuhong Guo, Russell Greiner, Dale Schuurmans
2005	—	`conf`	Learning a Dynamic Classification Method to Detect Faces and Identify Facial Expression. AMFG Ramana Isukapalli, Ahmed M. Elgammal, Russell Greiner
2005	—	`conf`	Learning and Classifying Under Hard Budgets. ECML Aloak Kapoor, Russell Greiner
2005	—	`conf`	Off-line Evaluation of Recommendation Functions. User Modeling Tingshao Zhu, Russell Greiner, Gerald Häubl, Kevin Jewell, Robert Price
2005	J	`jnl`	PA-GOSUB: a searchable database of model organism protein sequences with their predicted Gene Ontology molecular function and subcellular localization. Nucleic Acids Res. Paul Lu, Duane Szafron, Russell Greiner, David S. Wishart, Alona Fyshe, Brandon Pearcy, Brett Poulin, Roman Eisner, Danny Ngo, Nicholas Lamb
2005	—	`conf`	Segmenting Brain Tumors with Conditional Random Fields and Support Vector Machines. CVBIA Chi-Hoon Lee, Mark Schmidt, Albert Murtha, Aalo Bistritz, Jörg Sander, Russell Greiner
2005	C	`conf`	Segmenting brain tumors using alignment-based features. ICMLA Mark Schmidt, Ilya Levner, Russell Greiner, Albert Murtha, Aalo Bistritz
2005	J	`jnl`	Structural Extension to Logistic Regression: Discriminative Parameter Learning of Belief Net Classifiers. Mach. Learn. Russell Greiner, Xiaoyuan Su, Bin Shen, Wei Zhou
2005	—	`conf`	Support Vector Random Fields for Spatial Classification. PKDD Chi-Hoon Lee, Russell Greiner, Mark Schmidt
2005	A*	`conf`	The Proteome Analyst Suite of Automated Function Prediction Tools. AAAI Brett Poulin, Duane Szafron, Paul Lu, Russell Greiner, David S. Wishart, Roman Eisner, Alona Fyshe, Brandon Pearcy, Luca Pireddu
2005	A*	`conf`	Using Learned Browsing Behavior Models to Recommend Relevant Web Pages. IJCAI Tingshao Zhu, Russell Greiner, Gerald Häubl, Kevin Jewell, Robert Price
2004	A	`conf`	Active Model Selection. UAI Omid Madani, Daniel J. Lizotte, Russell Greiner
2004	—	`conf`	Batch Reinforcement Learning with State Importance. ECML Lihong Li, Vadim Bulitko, Russell Greiner
2004	—	`conf`	Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields. ISCSLP Shaojun Wang, Shaomin Wang, Russell Greiner, Dale Schuurmans, Li Cheng
2004	J	`jnl`	Predicting subcellular localization of proteins using machine-learned classifiers. Bioinform. Zhiyong Lu, Duane Szafron, Russell Greiner, Paul Lu, David S. Wishart, Brett Poulin, John Anvik, Cam Macdonell, Roman Eisner
2004	J	`jnl`	Proteome Analyst: custom predictions with explanations in a web-based tool for high-throughput proteome annotations. Nucleic Acids Res. Duane Szafron, Paul Lu, Russell Greiner, David S. Wishart, Brett Poulin, Roman Eisner, Zhiyong Lu, John Anvik, Cam Macdonell, Alona Fyshe, David Meeuwis
2004	A*	`conf`	The Budgeted Multi-armed Bandit Problem. COLT Omid Madani, Daniel J. Lizotte, Russell Greiner
2003	—	`conf`	An Effective Complete-Web Recommender System. WWW (Alternate Paper Tracks) Tingshao Zhu, Russell Greiner, Gerald Häubl
2003	A	`conf`	Budgeted Learning of Naive-Bayes Classifiers. UAI Daniel J. Lizotte, Omid Madani, Russell Greiner
2003	B	`conf`	Discriminative Parameter Learning of General Bayesian Network Classifiers. ICTAI Bin Shen, Xiaoyuan Su, Russell Greiner, Petr Musílek, Corrine Cheng
2003	—	`conf`	Learning a Model of a Web User's Interests. User Modeling Tingshao Zhu, Russell Greiner, Gerald Häubl
2003	A*	`conf`	Lookahead Pathologies for Single Agent Search. IJCAI Vadim Bulitko, Lihong Li, Russell Greiner, Ilya Levner
2003	—	`conf`	Predicting Web Information Content. ITWP Tingshao Zhu, Russell Greiner, Gerald Häubl, Robert Price
2003	—	`conf`	Towards Automated Creation of Image Interpretation Systems. Australian Conference on Artificial Intelligence Ilya Levner, Vadim Bulitko, Lihong Li, Greg Lee, Russell Greiner
2003	A*	`conf`	Use of Off-line Dynamic Programming for Efficient Image Interpretation. IJCAI Ramana Isukapalli, Russell Greiner
2002	J	`jnl`	Learning Bayesian networks from data: An information-theory based approach. Artif. Intell. Jie Cheng, Russell Greiner, Jonathan Kelly, David A. Bell, Weiru Liu
2002	J	`jnl`	Learning cost-sensitive active classifiers. Artif. Intell. Russell Greiner, Adam J. Grove, Dan Roth
2002	—	`conf`	Optimal Depth-First Strategies for And-Or Trees. AAAI/IAAI Russell Greiner, Ryan Hayward, Michael Molloy
2002	—	`conf`	Performance of Lookahead Control Policies in the Face of Abstractions and Approximations. SARA Ilya Levner, Vadim Bulitko, Omid Madani, Russell Greiner
2002	—	`conf`	Structural Extension to Logistic Regression: Discriminative Parameter Learning of Belief Net Classifiers. AAAI/IAAI Russell Greiner, Wei Zhou
2001	A	`conf`	Bayesian Error-Bars for Belief Net Inference. UAI Tim Van Allen, Russell Greiner, Peter Hooper
2001	A*	`conf`	Efficient Car Recognition Policies. ICRA Ramana Isukapalli, Russell Greiner
2001	A*	`conf`	Efficient Interpretation Policies. IJCAI Ramana Isukapalli, Russell Greiner
2001	J	`jnl`	Efficient reasoning. ACM Comput. Surv. Russell Greiner, Christian Darken, N. Iwan Santoso
2001	Misc	`conf`	Learning Bayesian Belief Network Classifiers: Algorithms and System. AI Jie Cheng, Russell Greiner
2000	A*	`conf`	Model Selection Criteria for Learning Belief Nets: An Empirical Comparison. ICML Tim Van Allen, Russell Greiner
2000	—	`conf`	Predicting UNIX Command Lines: Adjusting to User Patterns. AAAI/IAAI Benjamin Korvemaker, Russell Greiner
1999	A	`conf`	Comparing Bayesian Network Classifiers. UAI Jie Cheng, Russell Greiner
1999	J	`jnl`	The Complexity of Revising Logic Programs. J. Log. Program. Russell Greiner
1997	J	`jnl`	Knowing what doesn't Matter: Exploiting the Omission of Irrelevant Data. Artif. Intell. Russell Greiner, Adam J. Grove, Alexander Kogan
1997	A	`conf`	Learning Bayesian Nets that Perform Well. UAI Russell Greiner, Adam J. Grove, Dale Schuurmans
1997	J	`jnl`	The Relevance of Relevance (Editorial). Artif. Intell. Devika Subramanian, Russell Greiner, Judea Pearl
1997	A*	`conf`	Why Experimentation can be better than "Perfect Guidance". ICML Tobias Scheffer, Russell Greiner, Christian Darken
1996	A*	`conf`	Exploiting the Omission of Irrelevant Data. ICML Russell Greiner, Adam J. Grove, Alexander Kogan
1996	A*	`conf`	Learning Active Classifiers. ICML Russell Greiner, Adam J. Grove, Dan Roth
1996	J	`jnl`	Learning to select useful landmarks. IEEE Trans. Syst. Man Cybern. Part B Russell Greiner, Ramana Isukapalli
1996	J	`jnl`	PALO: A Probabilistic Hill-Climbing Algorithm. Artif. Intell. Russell Greiner
1996	J	`jnl`	Probably Approximately Optimal Satisficing Strategies. Artif. Intell. Russell Greiner, Pekka Orponen
1995	A*	`conf`	Practical PAC Learning. IJCAI Dale Schuurmans, Russell Greiner
1995	A*	`conf`	Sequential PAC Learning. COLT Dale Schuurmans, Russell Greiner
1995	A*	`conf`	The Challenge of Revising an Impure Theory. ICML Russell Greiner
1995	A*	`conf`	The Complexity of Theory Revision. IJCAI Russell Greiner
1994	A*	`conf`	Learning to Select Useful Landmarks. AAAI Russell Greiner, Ramana Isukapalli
1993	J	`jnl`	D. B. Lenat and R. V. Guha, Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project. Artif. Intell. Charles Elkan, Russell Greiner
1992	A*	`conf`	A Statistical Approach to Solving the EBL Utility Problem. AAAI Russell Greiner, Igor Jurisica
1992	A*	`conf`	Learning Efficient Query Processing Strategies. PODS Russell Greiner
1992	A*	`conf`	Learning Useful Horn Approximations. KR Russell Greiner, Dale Schuurmans
1992	—	`conf`	Learning an Optimally Accurate Representation System. ECAI Workshop on Knowledge Representation and Reasoning Russell Greiner, Dale Schuurmans
1991	J	`jnl`	Finding Optimal Derivation Strategies in Redundant Knowledge Bases. Artif. Intell. Russell Greiner
1991	A*	`conf`	Measuring and Improving the Effectiveness of Representations. IJCAI Russell Greiner, Charles Elkan
1991	A*	`conf`	Probably Approximately Optimal Derivation Strategies. KR Russell Greiner, Pekka Orponen
1990	A*	`conf`	On the Sample Complexity of Finding Good Search Strategies. COLT Pekka Orponen, Russell Greiner
1989	J	`jnl`	A Correction to the Algorithm in Reiter's Theory of Diagnosis. Artif. Intell. Russell Greiner, Barbara A. Smith, Ralph W. Wilkerson
1989	A*	`conf`	Incorporating Redundant Learned Rules: A Preliminary Formal Analysis of EBL. IJCAI Russell Greiner, J. Likuski
1989	—	`conf`	Towards a Formal Analysis of EBL. ML Russell Greiner
1988	J	`jnl`	A Review of Machine Learning at AAAI-87. Mach. Learn. Russell Greiner
1988	J	`jnl`	Against the unjustified use of probabilities. Comput. Intell. Russell Greiner
1988	J	`jnl`	Learning by Understanding Analogies. Artif. Intell. Russell Greiner
1988	Misc	`conf`	Signal abstractions in the machine analysis of radar signals for ice profiling. ICASSP S. Lee, Evangelos E. Milios, Russell Greiner, James R. Rossiter
1985	—	`—`	Learning by understanding analogies. Russell Greiner
1983	A*	`conf`	What's New? A Semantic Definition of Novelty. IJCAI Russell Greiner, Michael R. Genesereth
1980	A*	`conf`	A Representation Language Language. AAAI Russell Greiner, Douglas B. Lenat