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ORCIDRussell Greiner
Russ Greiner
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- affiliation: University of Alberta, Edmonton, Canada
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2020 – today
- 2021
[j59]Yaqian Long, Benoit Rivard, Arturo Sanchez-Azofeifa, Russell Greiner, Dominica Harrison, Sen Jia:
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 97: 102286 (2021)- [j58]Mohsen Soltanpour
, Russ Greiner, Pierre Boulanger, Brian Buck:
Improvement of automatic ischemic stroke lesion segmentation in CT perfusion maps using a learned deep neural network. Comput. Biol. Medicine 137: 104849 (2021) - [j57]Zehra Shah, Jeffrey Sawalha, Mashrura Tasnim, Shiang Qi, Eleni Stroulia, Russell Greiner:
Learning Language and Acoustic Models for Identifying Alzheimer's Dementia From Speech. Frontiers Comput. Sci. 3: 624659 (2021) - [j56]Neil C. Borle, Edmond A. Ryan, Russell Greiner:
The challenge of predicting blood glucose concentration changes in patients with type I diabetes. Health Informatics J. 27(1): 146045822097758 (2021) - [j55]Siyang Tian, Xuan Cao, Russell Greiner, Carin Li, Anchi Guo, David S. Wishart:
CyProduct: A Software Tool for Accurately Predicting the Byproducts of Human Cytochrome P450 Metabolism. J. Chem. Inf. Model. 61(6): 3128-3140 (2021) - [j54]Michael A. Skinnider, Fei Wang, Daniel Pasin, Russell Greiner, Leonard J. Foster, Petur W. Dalsgaard, David S. Wishart:
A deep generative model enables automated structure elucidation of novel psychoactive substances. Nat. Mach. Intell. 3(11): 973-984 (2021) - [c127]Roberto Vega, Pouneh Gorji, Zichen Vincent Zhang, Xuebin Qin, Abhilash Rakkunedeth Hareendranathan, Jeevesh Kapur, Jacob L. Jaremko, Russell Greiner:
Sample efficient learning of image-based diagnostic classifiers via probabilistic labels. AISTATS 2021: 739-747 - [i28]Roberto Vega, Pouneh Gorji, Zichen Vincent Zhang, Xuebin Qin, Abhilash Rakkunedeth Hareendranathan, Jeevesh Kapur, Jacob L. Jaremko, Russell Greiner:
Sample Efficient Learning of Image-Based Diagnostic Classifiers Using Probabilistic Labels. CoRR abs/2102.06164 (2021) - [i27]Roberto Vega, Leonardo Flores, Russell Greiner:
SIMLR: Machine Learning inside the SIR model for COVID-19 Forecasting. CoRR abs/2106.01590 (2021) - [i26]Negar Hassanpour, Russell Greiner:
Variational Auto-Encoder Architectures that Excel at Causal Inference. CoRR abs/2111.06486 (2021) - 2020
- [j53]Humza Haider, Bret Hoehn, Sarah Davis, Russell Greiner:
Effective Ways to Build and Evaluate Individual Survival Distributions. J. Mach. Learn. Res. 21: 85:1-85:63 (2020) - [c126]Negar Hassanpour, Russell Greiner:
Learning Disentangled Representations for CounterFactual Regression. ICLR 2020 - [c125]Junfeng Wen, Russell Greiner, Dale Schuurmans:
Domain Aggregation Networks for Multi-Source Domain Adaptation. ICML 2020: 10214-10224 - [c124]Muhammad Yousefnezhad, Alessandro Selvitella, Daoqiang Zhang, Andrew J. Greenshaw, Russell Greiner:
Shared Space Transfer Learning for analyzing multi-site fMRI data. NeurIPS 2020 - [i25]Muhammad Yousefnezhad, Alessandro Selvitella, Daoqiang Zhang, Andrew J. Greenshaw, Russell Greiner:
Shared Space Transfer Learning for analyzing multi-site fMRI data. CoRR abs/2010.15594 (2020)
2010 – 2019
- 2019
- [j52]Reyhaneh Ghoreishiamiri, Graham Little, Matthew R. G. Brown, Russell Greiner:
A simple classification framework for predicting Alzheimer's disease from region-based grey matter volume and APOE genotype status. Artif. Intell. Res. 8(2): 15- (2019) - [j51]Yannick Djoumbou Feunang, Jarlei Fiamoncini, Alberto Gil-de-la-Fuente, Russell Greiner, Claudine Manach, David S. Wishart:
BioTransformer: a comprehensive computational tool for small molecule metabolism prediction and metabolite identification. J. Cheminformatics 11(1): 2:1-2:25 (2019) - [j50]Jakub M. Tomczak, Szymon Zareba, Siamak Ravanbakhsh, Russell Greiner:
Low-Dimensional Perturb-and-MAP Approach for Learning Restricted Boltzmann Machines. Neural Process. Lett. 50(2): 1401-1419 (2019) - [c123]Mohsen Soltanpour, Russell Greiner, Pierre Boulanger, Brian Buck:
Ischemic Stroke Lesion Prediction in CT Perfusion Scans Using Multiple Parallel U-Nets Following by a Pixel-Level Classifier. BIBE 2019: 957-963 - [c122]Negar Hassanpour, Russell Greiner:
CounterFactual Regression with Importance Sampling Weights. IJCAI 2019: 5880-5887 - [c121]Samuel Sokota, Ryan D'Orazio, Khurram Javed, Humza Haider, Russell Greiner:
Simultaneous Prediction Intervals for Patient-Specific Survival Curves. IJCAI 2019: 5975-5981 - [c120]Farzane Aminmansour, Andrew Patterson, Lei Le, Yisu Peng, Daniel Mitchell, Franco Pestilli, Cesar F. Caiafa, Russell Greiner, Martha White:
Learning Macroscopic Brain Connectomes via Group-Sparse Factorization. NeurIPS 2019: 8847-8857 - [i24]Luke N. Kumar, Russell Greiner:
Gene Expression based Survival Prediction for Cancer Patients: A Topic Modeling Approach. CoRR abs/1903.10536 (2019) - [i23]Neil C. Borle, Edmond A. Ryan, Russell Greiner:
The Challenge of Predicting Meal-to-meal Blood Glucose Concentrations for Patients with Type I Diabetes. CoRR abs/1903.12347 (2019) - [i22]Samuel Sokota, Ryan D'Orazio, Khurram Javed, Humza Haider, Russell Greiner:
Simultaneous Prediction Intervals for Patient-Specific Survival Curves. CoRR abs/1906.10780 (2019) - [i21]Seyedeh Sepideh Emam, Amy X. Du, Philip Surmanowicz, Simon F. Thomsen, Russ Greiner, Robert Gniadecki:
Predicting the Long-Term Outcomes of Biologics in Psoriasis Patients Using Machine Learning. CoRR abs/1908.09251 (2019) - [i20]Junfeng Wen, Russell Greiner, Dale Schuurmans:
Domain Aggregation Networks for Multi-Source Domain Adaptation. CoRR abs/1909.05352 (2019) - [i19]Zichen Zhang, Qingfeng Lan, Lei Ding, Yue Wang, Negar Hassanpour, Russell Greiner:
Reducing Selection Bias in Counterfactual Reasoning for Individual Treatment Effects Estimation. CoRR abs/1912.09040 (2019) - 2018
- [j49]Neil C. Borle, Meysam Feghhi, Eleni Stroulia, Russell Greiner, Abram Hindle:
Analyzing the effects of test driven development in GitHub. Empir. Softw. Eng. 23(4): 1931-1958 (2018) - [j48]Siyang Tian, Yannick Djoumbou Feunang, Russell Greiner, David S. Wishart:
CypReact: A Software Tool for in Silico Reactant Prediction for Human Cytochrome P450 Enzymes. J. Chem. Inf. Model. 58(6): 1282-1291 (2018) - [c119]Negar Hassanpour, Russell Greiner:
A Novel Evaluation Methodology for Assessing Off-Policy Learning Methods in Contextual Bandits. Canadian Conference on AI 2018: 31-44 - [c118]Neil C. Borle, Meysam Feghhi, Eleni Stroulia, Russell Greiner, Abram Hindle:
Analyzing the effects of test driven development in GitHub. ICSE 2018: 1062 - [c117]Roberto Vega, Russell Greiner:
Finding Effective Ways to (Machine) Learn fMRI-Based Classifiers from Multi-site Data. MLCN/DLF/iMIMIC@MICCAI 2018: 32-39 - [i18]Humza Haider, Bret Hoehn, Sarah Davis, Russell Greiner:
Effective Ways to Build and Evaluate Individual Survival Distributions. CoRR abs/1811.11347 (2018) - 2017
- [j47]Roberto Vega, Touqir Sajed, Kory Wallace Mathewson, Kriti Khare, Patrick M. Pilarski, Russell Greiner, Gildardo Sánchez-Ante, Javier Mauricio Antelis:
Assessment of feature selection and classification methods for recognizing motor imagery tasks from electroencephalographic signals. Artif. Intell. Res. 6(1): 37-51 (2017) - [j46]Karan Aggarwal, Finbarr Timbers, Tanner Rutgers, Abram Hindle, Eleni Stroulia, Russell Greiner:
Detecting duplicate bug reports with software engineering domain knowledge. J. Softw. Evol. Process. 29(3) (2017) - [c116]Stephen Romansky, Neil C. Borle, Shaiful Alam Chowdhury, Abram Hindle, Russell Greiner:
Deep Green: Modelling Time-Series of Software Energy Consumption. ICSME 2017: 273-283 - [c115]Mina Gheiratmand, Irina Rish, Guillermo A. Cecchi, Matthew R. G. Brown, Russell Greiner, Pouya Bashivan, Pablo Polosecki, Serdar M. Dursun:
Learning discriminative functional network features of schizophrenia. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2017: 101371A - [i17]Jumana Dakka, Pouya Bashivan, Mina Gheiratmand, Irina Rish, Shantenu Jha, Russell Greiner:
Learning Neural Markers of Schizophrenia Disorder Using Recurrent Neural Networks. CoRR abs/1712.00512 (2017) - 2016
- [j45]Yannick Djoumbou, Roman Eisner, Craig Knox, Leonid L. Chepelev, Janna Hastings, Gareth Owen, Eoin Fahy, Christoph Steinbeck, Shankar Subramanian, Evan Bolton, Russell Greiner, David S. Wishart:
ClassyFire: automated chemical classification with a comprehensive, computable taxonomy. J. Cheminformatics 8(1): 61:1-61:20 (2016) - [c114]Siamak Ravanbakhsh, Barnabás Póczos, Jeff G. Schneider, Dale Schuurmans, Russell Greiner:
Stochastic Neural Networks with Monotonic Activation Functions. AISTATS 2016: 809-818 - [c113]Siamak Ravanbakhsh, Barnabás Póczos, Russell Greiner:
Boolean Matrix Factorization and Noisy Completion via Message Passing. ICML 2016: 945-954 - [i16]Siamak Ravanbakhsh, Barnabás Póczos, Jeff G. Schneider, Dale Schuurmans, Russell Greiner:
Stochastic Neural Networks with Monotonic Activation Functions. CoRR abs/1601.00034 (2016) - 2015
- [j44]Siamak Ravanbakhsh, Russell Greiner:
Perturbed message passing for constraint satisfaction problems. J. Mach. Learn. Res. 16: 1249-1274 (2015) - [c112]Shaiful Alam Chowdhury, Luke N. Kumar, Md. Toukir Imam, Mohomed Shazan Mohomed Jabbar, Varun Sapra, Karan Aggarwal, Abram Hindle, Russell Greiner:
A system-call based model of software energy consumption without hardware instrumentation. IGSC 2015: 1-6 - [c111]Junfeng Wen, Russell Greiner, Dale Schuurmans:
Correcting Covariate Shift with the Frank-Wolfe Algorithm. IJCAI 2015: 1010-1016 - [c110]Karan Aggarwal, Tanner Rutgers, Finbarr Timbers, Abram Hindle, Russell Greiner, Eleni Stroulia:
Detecting duplicate bug reports with software engineering domain knowledge. SANER 2015: 211-220 - [i15]Siamak Ravanbakhsh, Russell Greiner:
Boolean Matrix Factorization and Completion via Message Passing. CoRR abs/1509.08535 (2015) - 2014
- [j43]Felicity Allen, Allison Pon, Michael Wilson, Russell Greiner, David S. Wishart:
CFM-ID: a web server for annotation, spectrum prediction and metabolite identification from tandem mass spectra. Nucleic Acids Res. 42(Webserver-Issue): 94-99 (2014) - [c109]Sheehan Khan, Russell Greiner:
The Budgeted Biomarker Discovery Problem: A Variant of Association Studies. AAAI Workshop: Modern Artificial Intelligence for Health Analytics 2014 - [c108]Sheehan Khan, Russell Greiner:
Budgeted transcript discovery: A framework for joint exploration and validation studies. BIBM 2014: 188-191 - [c107]Baidya Nath Saha, Amritpal Saini, Nilanjan Ray, Russell Greiner, Judith Hugh, Mauro Tambasco:
A robust convergence index filter for breast cancer cell segmentation. ICIP 2014: 922-926 - [c106]Junfeng Wen, Chun-Nam Yu, Russell Greiner:
Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification. ICML 2014: 631-639 - [c105]Siamak Ravanbakhsh, Christopher Srinivasa, Brendan J. Frey, Russell Greiner:
Min-Max Problems on Factor Graphs. ICML 2014: 1035-1043 - [c104]Kun Deng, Russ Greiner, Susan A. Murphy:
Budgeted Learning for Developing Personalized Treatment. ICMLA 2014: 7-14 - [c103]Siamak Ravanbakhsh, Reihaneh Rabbany, Russell Greiner:
Augmentative Message Passing for Traveling Salesman Problem and Graph Partitioning. NIPS 2014: 289-297 - [i14]Siamak Ravanbakhsh, Russell Greiner:
Perturbed Message Passing for Constraint Satisfaction Problems. CoRR abs/1401.6686 (2014) - [i13]Siamak Ravanbakhsh, Russell Greiner, Brendan J. Frey:
Training Restricted Boltzmann Machine by Perturbation. CoRR abs/1405.1436 (2014) - [i12]Siamak Ravanbakhsh, Reihaneh Rabbany, Russell Greiner:
Augmentative Message Passing for Traveling Salesman Problem and Graph Partitioning. CoRR abs/1406.0941 (2014) - [i11]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:
Accurate, fully-automated NMR spectral profiling for metabolomics. CoRR abs/1409.1456 (2014) - [i10]Siamak Ravanbakhsh, Russell Greiner:
Algebra of inference in graphical models revisited. CoRR abs/1409.7410 (2014) - 2013
- [j42]Mohsen Hajiloo, Yadav Sapkota, John R. Mackey, Paula Robson, Russell Greiner, Sambasivarao Damaraju:
ETHNOPRED: a novel machine learning method for accurate continental and sub-continental ancestry identification and population stratification correction. BMC Bioinform. 14: 61 (2013) - [j41]Mohsen Hajiloo, Babak Damavandi, Metanat HooshSadat, Farzad Sangi, John R. Mackey, Carol E. Cass, Russell Greiner, Sambasivarao Damaraju:
Breast cancer prediction using genome wide single nucleotide polymorphism data. BMC Bioinform. 14(S-13): S3 (2013) - [j40]Shaojun Wang, Shaomin Wang, Li Cheng, Russell Greiner, Dale Schuurmans:
Exploiting Syntactic, Semantic, and Lexical Regularities in Language Modeling via Directed Markov Random Fields. Comput. Intell. 29(4): 649-679 (2013) - [j39]Shaojun Wang, Russell Greiner, Shaomin Wang:
Consistency and Generalization Bounds for Maximum Entropy Density Estimation. Entropy 15(12): 5439-5463 (2013) - [j38]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:
HMDB 3.0 - The Human Metabolome Database in 2013. Nucleic Acids Res. 41(Database-Issue): 801-807 (2013) - [c102]Marius Stanescu, Sergio Poo Hernandez, Graham Erickson, Russell Greiner, Michael Buro:
Predicting Army Combat Outcomes in StarCraft. AIIDE 2013 - [c101]Idanis Diaz, Pierre Boulanger, Russell Greiner, Bret Hoehn, Lindsay Rowe, Albert Murtha:
An automatic brain tumor segmentation tool. EMBC 2013: 3339-3342 - [c100]Sheehan Khan, Russell Greiner:
Finding Discriminatory Genes: A Methodology for Validating Microarray Studies. ICDM Workshops 2013: 64-71 - [c99]Mohamed Ben Salah, Idanis Diaz, Russell Greiner, Pierre Boulanger, Bret Hoehn, Albert Murtha:
Fully Automated Brain Tumor Segmentation Using Two MRI Modalities. ISVC (1) 2013: 30-39 - [c98]Navid Zolghadr, Gábor Bartók, Russell Greiner, András György, Csaba Szepesvári:
Online Learning with Costly Features and Labels. NIPS 2013: 1241-1249 - [i9]Tim Van Allen, Russell Greiner, Peter Hooper:
Bayesian Error-Bars for Belief Net Inference. CoRR abs/1301.2313 (2013) - [i8]Jie Cheng, Russell Greiner:
Comparing Bayesian Network Classifiers. CoRR abs/1301.6684 (2013) - [i7]Russell Greiner, Adam J. Grove, Dale Schuurmans:
Learning Bayesian Nets that Perform Well. CoRR abs/1302.1542 (2013) - [i6]Felicity Allen, Russell Greiner, David S. Wishart:
Competitive Fragmentation Modeling of ESI-MS/MS spectra for metabolite identification. CoRR abs/1312.0264 (2013) - 2012
- [j37]Baidya Nath Saha, Nilanjan Ray, Russell Greiner, Albert Murtha, Hong Zhang:
Quick detection of brain tumors and edemas: A bounding box method using symmetry. Comput. Medical Imaging Graph. 36(2): 95-107 (2012) - [j36]Ashkan Zarnani, Petr Musílek, Xiaoyu Shi, Xiaodi Ke, Hua He, Russell Greiner:
Learning to predict ice accretion on electric power lines. Eng. Appl. Artif. Intell. 25(3): 609-617 (2012) - [j35]Davoud Moulavi, Mohsen Hajiloo, Jörg Sander, Philip F. Halloran, Russell Greiner:
Combining gene expression and interaction network data to improve kidney lesion score prediction. Int. J. Bioinform. Res. Appl. 8(1/2): 54-66 (2012) - [j34]Daniel J. Lizotte, Russell Greiner, Dale Schuurmans:
An experimental methodology for response surface optimization methods. J. Glob. Optim. 53(4): 699-736 (2012) - [c97]Siamak Ravanbakhsh, Chun-Nam Yu, Russell Greiner:
A Generalized Loop Correction Method for Approximate Inference in Graphical Models. ICML 2012 - [i5]Peter Hooper, Yasin Abbasi-Yadkori, Russell Greiner, Bret Hoehn:
Improved Mean and Variance Approximations for Belief Net Responses via Network Doubling. CoRR abs/1205.2642 (2012) - [i4]Alejandro Isaza, Csaba Szepesvári, Vadim Bulitko, Russell Greiner:
Speeding Up Planning in Markov Decision Processes via Automatically Constructed Abstractions. CoRR abs/1206.3233 (2012) - [i3]Siamak Ravanbakhsh, Chun-Nam Yu, Russell Greiner:
A Generalized Loop Correction Method for Approximate Inference in Graphical Models. CoRR abs/1206.4654 (2012) - [i2]Omid Madani, Daniel J. Lizotte, Russell Greiner:
Active Model Selection. CoRR abs/1207.4138 (2012) - [i1]Daniel J. Lizotte, Omid Madani, Russell Greiner:
Budgeted Learning of Naive-Bayes Classifiers. CoRR abs/1212.2472 (2012) - 2011
- [c96]Idanis Diaz, Pierre Boulanger, Russell Greiner, Albert Murtha:
A critical review of the effects of de-noising algorithms on MRI brain tumor segmentation. EMBC 2011: 3934-3937 - [c95]Chun-Nam Yu, Russell Greiner, Hsiu-Chin Lin, Vickie Baracos:
Learning Patient-Specific Cancer Survival Distributions as a Sequence of Dependent Regressors. NIPS 2011: 1845-1853 - [c94]Xiaoyuan Su, Russell Greiner, Taghi M. Khoshgoftaar, Amri Napolitano:
Using Classifier-Based Nominal Imputation to Improve Machine Learning. PAKDD (1) 2011: 124-135 - 2010
- [j33]Oliver Schulte, Wei Luo, Russell Greiner:
Mind change optimal learning of Bayes net structure from dependency and independency data. Inf. Comput. 208(1): 63-82 (2010) - [c93]Siamak (Moshen) Ravanbakhsh, Barnabás Póczos, Russell Greiner:
A Cross-Entropy Method that Optimizes Partially Decomposable Problems: A New Way to Interpret NMR Spectra. AAAI 2010 - [c92]Oliver Schulte, Gustavo Frigo, Russell Greiner, Hassan Khosravi:
The IMAP Hybrid Method for Learning Gaussian Bayes Nets. Canadian Conference on AI 2010: 123-134 - [c91]Liuyang Li, Barnabás Póczos, Csaba Szepesvári, Russell Greiner:
Budgeted Distribution Learning of Belief Net Parameters. ICML 2010: 879-886
2000 – 2009
- 2009
- [j32]Babak Bostan, Russell Greiner, Duane Szafron, Paul Lu:
Predicting homologous signaling pathways using machine learning. Bioinform. 25(22): 2913-2920 (2009) - [j31]Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greiner:
Making an accurate classifier ensemble by voting on classifications from imputed learning sets. Int. J. Inf. Decis. Sci. 1(3): 301-322 (2009) - [j30]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:
HMDB: a knowledgebase for the human metabolome. Nucleic Acids Res. 37(Database-Issue): 603-610 (2009) - [c90]Tingshao Zhu, Russell Greiner, Bin Hu:
LILAC - Learn from Internet: Log, Annotation, and Content. AAAI Spring Symposium: Experimental Design for Real-World Systems 2009: 57- - [c89]Aliaksei Kerhet, Cormac Small, Harvey Quon, Terence Riauka, Russell Greiner, Alexander McEwan, Wilson Roa:
Segmentation of Lung Tumours in Positron Emission Tomography Scans: A Machine Learning Approach. AIME 2009: 146-155 - [c88]Oliver Schulte, Gustavo Frigo, Russell Greiner, Wei Luo, Hassan Khosravi:
A new hybrid method for Bayesian network learning With dependency constraints. CIDM 2009: 53-60 - [c87]Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greiner:
VipBoost: A More Accurate Boosting Algorithm. FLAIRS Conference 2009 - [c86]Alireza Farhangfar, Russell Greiner, Csaba Szepesvári:
Learning to segment from a few well-selected training images. ICML 2009: 305-312 - [c85]Barnabás Póczos, Yasin Abbasi-Yadkori, Csaba Szepesvári, Russell Greiner, Nathan R. Sturtevant:
Learning when to stop thinking and do something! ICML 2009: 825-832 - [c84]Peter Hooper, Yasin Abbasi-Yadkori, Russell Greiner, Bret Hoehn:
Improved Mean and Variance Approximations for Belief Net Responses via Network Doubling. UAI 2009: 232-239 - 2008
- [j29]Tim Van Allen, Ajit Singh, Russell Greiner, Peter Hooper:
Quantifying the uncertainty of a belief net response: Bayesian error-bars for belief net inference. Artif. Intell. 172(4-5): 483-513 (2008) - [j28]Alona Fyshe, Yifeng Liu, Duane Szafron, Russell Greiner, Paul Lu:
Improving subcellular localization prediction using text classification and the gene ontology. Bioinform. 24(21): 2512-2517 (2008) - [j27]Ilya Levner, Hong Zhang, Russell Greiner:
Heterogeneous Stacking for Classification-Driven Watershed Segmentation. EURASIP J. Adv. Signal Process. 2008 (2008) - [j26]Chi-Hoon Lee, Osmar R. Zaïane, Ho-Hyun Park, Jiayuan Huang, Russell Greiner:
Clustering high dimensional data: A graph-based relaxed optimization approach. Inf. Sci. 178(23): 4501-4511 (2008) - [c83]Chi-Hoon Lee, Matthew R. G. Brown, Russell Greiner, Shaojun Wang, Albert Murtha:
Constrained Classification on Structured Data. AAAI 2008: 1812-1813 - [c82]Alejandro Isaza, Jieshan Lu, Vadim Bulitko, Russell Greiner:
A Cover-Based Approach to Multi-Agent Moving Target Pursuit. AIIDE 2008 - [c81]Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greiner:
A Mixture Imputation-Boosted Collaborative Filter. FLAIRS Conference 2008: 312-316 - [c80]Ilya Levner, Russell Greiner, Hong Zhang:
Supervised image segmentation via ground truth decomposition. ICIP 2008: 737-740 - [c79]John D. Lees-Miller, Fraser Anderson, Bret Hoehn, Russell Greiner:
Does Wikipedia Information Help Netflix Predictions? ICMLA 2008: 337-343 - [c78]Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greiner:
Using Imputation Techniques to Help Learn Accurate Classifiers. ICTAI (1) 2008: 437-444 - [c77]Alireza Farhangfar, Russell Greiner, Martin Zinkevich:
A Fast Way to Produce Optimal Fixed-Depth Decision Trees. ISAIM 2008 - [c76]Chi-Hoon Lee, Shaojun Wang, Albert Murtha, Matthew R. G. Brown, Russell Greiner:
Segmenting Brain Tumors Using Pseudo-Conditional Random Fields. MICCAI (1) 2008: 359-366 - [c75]Xiaoyuan Su, Taghi M. Khoshgoftaar, Xingquan Zhu, Russell Greiner:
Imputation-boosted collaborative filtering using machine learning classifiers. SAC 2008: 949-950 - [c74]Alejandro Isaza, Csaba Szepesvári, Vadim Bulitko, Russell Greiner:
Speeding Up Planning in Markov Decision Processes via Automatically Constructed Abstraction. UAI 2008: 306-314 - [c73]Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greiner:
Imputed Neighborhood Based Collaborative Filtering. Web Intelligence 2008: 633-639 - 2007
- [j25]Lihong Li, Vadim Bulitko, Russell Greiner:
Focus of Attention in Reinforcement Learning. J. Univers. Comput. Sci. 13(9): 1246-1269 (2007) - [j24]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:
HMDB: the Human Metabolome Database. Nucleic Acids Res. 35(Database-Issue): 521-526 (2007) - [c72]Oliver Schulte, Wei Luo, Russell Greiner:
Mind Change Optimal Learning of Bayes Net Structure. COLT 2007: 187-202 - [c71]Yuhong Guo, Russell Greiner:
Optimistic Active-Learning Using Mutual Information. IJCAI 2007: 823-829 - [c70]David S. Wishart, Russell Greiner:
Session Introduction. Pacific Symposium on Biocomputing 2007: 112-114 - [c69]