Russell Greiner

According to our database1, Russell Greiner authored at least 174 papers between 1980 and 2019.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of two.

Timeline

Legend:

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Bibliography

2019
Low-Dimensional Perturb-and-MAP Approach for Learning Restricted Boltzmann Machines.
Neural Processing Letters, 2019

BioTransformer: a comprehensive computational tool for small molecule metabolism prediction and metabolite identification.
J. Cheminformatics, 2019

Domain Aggregation Networks for Multi-Source Domain Adaptation.
CoRR, 2019

Simultaneous Prediction Intervals for Patient-Specific Survival Curves.
CoRR, 2019

The Challenge of Predicting Meal-to-meal Blood Glucose Concentrations for Patients with Type I Diabetes.
CoRR, 2019

Gene Expression based Survival Prediction for Cancer Patients: A Topic Modeling Approach.
CoRR, 2019

CounterFactual Regression with Importance Sampling Weights.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018
Analyzing the effects of test driven development in GitHub.
Empirical Software Engineering, 2018

Effective Ways to Build and Evaluate Individual Survival Distributions.
CoRR, 2018

Analyzing the effects of test driven development in GitHub.
Proceedings of the 40th International Conference on Software Engineering, 2018

A Novel Evaluation Methodology for Assessing Off-Policy Learning Methods in Contextual Bandits.
Proceedings of the Advances in Artificial Intelligence, 2018

2017
Detecting duplicate bug reports with software engineering domain knowledge.
Journal of Software: Evolution and Process, 2017

Learning Neural Markers of Schizophrenia Disorder Using Recurrent Neural Networks.
CoRR, 2017

Learning discriminative functional network features of schizophrenia.
Proceedings of the Medical Imaging 2017: Biomedical Applications in Molecular, 2017

Deep Green: Modelling Time-Series of Software Energy Consumption.
Proceedings of the 2017 IEEE International Conference on Software Maintenance and Evolution, 2017

2016
ClassyFire: automated chemical classification with a comprehensive, computable taxonomy.
J. Cheminformatics, 2016

Stochastic Neural Networks with Monotonic Activation Functions.
CoRR, 2016

Boolean Matrix Factorization and Noisy Completion via Message Passing.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Perturbed message passing for constraint satisfaction problems.
J. Mach. Learn. Res., 2015

Boolean Matrix Factorization and Completion via Message Passing.
CoRR, 2015

Correcting Covariate Shift with the Frank-Wolfe Algorithm.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

A system-call based model of software energy consumption without hardware instrumentation.
Proceedings of the Sixth International Green and Sustainable Computing Conference, 2015

2014
CFM-ID: a web server for annotation, spectrum prediction and metabolite identification from tandem mass spectra.
Nucleic Acids Research, 2014

Augmentative Message Passing for Traveling Salesman Problem and Graph Partitioning.
CoRR, 2014

Accurate, fully-automated NMR spectral profiling for metabolomics.
CoRR, 2014

Training Restricted Boltzmann Machine by Perturbation.
CoRR, 2014

Algebra of inference in graphical models revisited.
CoRR, 2014

Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification.
Proceedings of the 31th International Conference on Machine Learning, 2014

Min-Max Problems on Factor Graphs.
Proceedings of the 31th International Conference on Machine Learning, 2014

A robust convergence index filter for breast cancer cell segmentation.
Proceedings of the 2014 IEEE International Conference on Image Processing, 2014

Budgeted transcript discovery: A framework for joint exploration and validation studies.
Proceedings of the 2014 IEEE International Conference on Bioinformatics and Biomedicine, 2014

The Budgeted Biomarker Discovery Problem: A Variant of Association Studies.
Proceedings of the Modern Artificial Intelligence for Health Analytics, 2014

2013
HMDB 3.0 - The Human Metabolome Database in 2013.
Nucleic Acids Research, 2013

Consistency and Generalization Bounds for Maximum Entropy Density Estimation.
Entropy, 2013

Learning Bayesian Nets that Perform Well
CoRR, 2013

Comparing Bayesian Network Classifiers
CoRR, 2013

Bayesian Error-Bars for Belief Net Inference
CoRR, 2013

Competitive Fragmentation Modeling of ESI-MS/MS spectra for metabolite identification.
CoRR, 2013

Exploiting Syntactic, Semantic, and Lexical Regularities in Language Modeling via Directed Markov Random Fields.
Computational Intelligence, 2013

ETHNOPRED: a novel machine learning method for accurate continental and sub-continental ancestry identification and population stratification correction.
BMC Bioinformatics, 2013

Breast cancer prediction using genome wide single nucleotide polymorphism data.
BMC Bioinformatics, 2013

Online Learning with Costly Features and Labels.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Fully Automated Brain Tumor Segmentation Using Two MRI Modalities.
Proceedings of the Advances in Visual Computing - 9th International Symposium, 2013

Finding Discriminatory Genes: A Methodology for Validating Microarray Studies.
Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013

An automatic brain tumor segmentation tool.
Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013

2012
An experimental methodology for response surface optimization methods.
J. Global Optimization, 2012

Combining gene expression and interaction network data to improve kidney lesion score prediction.
IJBRA, 2012

Learning to predict ice accretion on electric power lines.
Eng. Appl. of AI, 2012

Budgeted Learning of Naive-Bayes Classifiers
CoRR, 2012

Active Model Selection
CoRR, 2012

A Generalized Loop Correction Method for Approximate Inference in Graphical Models
CoRR, 2012

Speeding Up Planning in Markov Decision Processes via Automatically Constructed Abstractions
CoRR, 2012

Improved Mean and Variance Approximations for Belief Net Responses via Network Doubling
CoRR, 2012

Quick detection of brain tumors and edemas: A bounding box method using symmetry.
Comp. Med. Imag. and Graph., 2012

2011
Using Classifier-Based Nominal Imputation to Improve Machine Learning.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2011

Learning Patient-Specific Cancer Survival Distributions as a Sequence of Dependent Regressors.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

A critical review of the effects of de-noising algorithms on MRI brain tumor segmentation.
Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011

2010
Mind change optimal learning of Bayes net structure from dependency and independency data.
Inf. Comput., 2010

Budgeted Distribution Learning of Belief Net Parameters.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

The IMAP Hybrid Method for Learning Gaussian Bayes Nets.
Proceedings of the Advances in Artificial Intelligence, 2010

A Cross-Entropy Method that Optimizes Partially Decomposable Problems: A New Way to Interpret NMR Spectra.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009
HMDB: a knowledgebase for the human metabolome.
Nucleic Acids Research, 2009

Making an accurate classifier ensemble by voting on classifications from imputed learning sets.
IJIDS, 2009

Predicting homologous signaling pathways using machine learning.
Bioinformatics, 2009

Learning when to stop thinking and do something!
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Learning to segment from a few well-selected training images.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

VipBoost: A More Accurate Boosting Algorithm.
Proceedings of the Twenty-Second International Florida Artificial Intelligence Research Society Conference, 2009

A new hybrid method for Bayesian network learning With dependency constraints.
Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2009

Segmentation of Lung Tumours in Positron Emission Tomography Scans: A Machine Learning Approach.
Proceedings of the Artificial Intelligence in Medicine, 2009

LILAC - Learn from Internet: Log, Annotation, and Content.
Proceedings of the Experimental Design for Real-World Systems, 2009

2008
Clustering high dimensional data: A graph-based relaxed optimization approach.
Inf. Sci., 2008

Heterogeneous Stacking for Classification-Driven Watershed Segmentation.
EURASIP J. Adv. Sig. Proc., 2008

Improving subcellular localization prediction using text classification and the gene ontology.
Bioinformatics, 2008

Quantifying the uncertainty of a belief net response: Bayesian error-bars for belief net inference.
Artif. Intell., 2008

Imputed Neighborhood Based Collaborative Filtering.
Proceedings of the 2008 IEEE / WIC / ACM International Conference on Web Intelligence, 2008

Speeding Up Planning in Markov Decision Processes via Automatically Constructed Abstraction.
Proceedings of the UAI 2008, 2008

Imputation-boosted collaborative filtering using machine learning classifiers.
Proceedings of the 2008 ACM Symposium on Applied Computing (SAC), 2008

Segmenting Brain Tumors Using Pseudo-Conditional Random Fields.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2008

A Fast Way to Produce Optimal Fixed-Depth Decision Trees.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2008

Using Imputation Techniques to Help Learn Accurate Classifiers.
Proceedings of the 20th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2008), 2008

Does Wikipedia Information Help Netflix Predictions?
Proceedings of the Seventh International Conference on Machine Learning and Applications, 2008

Supervised image segmentation via ground truth decomposition.
Proceedings of the International Conference on Image Processing, 2008

A Mixture Imputation-Boosted Collaborative Filter.
Proceedings of the Twenty-First International Florida Artificial Intelligence Research Society Conference, 2008

A Cover-Based Approach to Multi-Agent Moving Target Pursuit.
Proceedings of the Fourth Artificial Intelligence and Interactive Digital Entertainment Conference, 2008

Constrained Classification on Structured Data.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007
HMDB: the Human Metabolome Database.
Nucleic Acids Research, 2007

Focus of Attention in Reinforcement Learning.
J. UCS, 2007

Hybrid Collaborative Filtering Algorithms Using a Mixture of Experts.
Proceedings of the 2007 IEEE / WIC / ACM International Conference on Web Intelligence, 2007

Session Introduction.
Proceedings of the Biocomputing 2007, 2007

Optimistic Active-Learning Using Mutual Information.
Proceedings of the IJCAI 2007, 2007

Mind Change Optimal Learning of Bayes Net Structure.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

2006
The Path-A metabolic pathway prediction web server.
Nucleic Acids Research, 2006

Learning a Classification-based Glioma Growth Model Using MRI Data.
JCP, 2006

Finding optimal satisficing strategies for and-or trees.
Artif. Intell., 2006

Efficient Spatial Classification Using Decoupled Conditional Random Fields.
Proceedings of the Knowledge Discovery in Databases: PKDD 2006, 2006

Information Marginalization on Subgraphs.
Proceedings of the Knowledge Discovery in Databases: PKDD 2006, 2006

Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Automatic construction of personalized customer interfaces.
Proceedings of the 11th International Conference on Intelligent User Interfaces, 2006

Learning Policies for Efficiently Identifying Objects of Many Classes.
Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006

Using query-specific variance estimates to combine Bayesian classifiers.
Proceedings of the Machine Learning, 2006

Stochastic Analysis of Lexical and Semantic Enhanced Structural Language Model.
Proceedings of the Grammatical Inference: Algorithms and Applications, 2006

Learning to Identify Facial Expression During Detection Using Markov Decision Process.
Proceedings of the Seventh IEEE International Conference on Automatic Face and Gesture Recognition (FGR 2006), 2006

Learning to Detect Objects of Many Classes Using Binary Classifiers.
Proceedings of the Computer Vision, 2006

A Classification-Based Glioma Diffusion Model Using MRI Data.
Proceedings of the Advances in Artificial Intelligence, 2006

Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling.
Proceedings of the ACL 2006, 2006

Visual Explanation of Evidence with Additive Classifiers.
Proceedings of the Proceedings, 2006

2005
PA-GOSUB: a searchable database of model organism protein sequences with their predicted Gene Ontology molecular function and subcellular localization.
Nucleic Acids Research, 2005

BASys: a web server for automated bacterial genome annotation.
Nucleic Acids Research, 2005

Structural Extension to Logistic Regression: Discriminative Parameter Learning of Belief Net Classifiers.
Machine Learning, 2005

Off-line Evaluation of Recommendation Functions.
Proceedings of the User Modeling 2005, 2005

Support Vector Random Fields for Spatial Classification.
Proceedings of the Knowledge Discovery in Databases: PKDD 2005, 2005

Using Learned Browsing Behavior Models to Recommend Relevant Web Pages.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Learning Coordination Classifiers.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Segmenting brain tumors using alignment-based features.
Proceedings of the Fourth International Conference on Machine Learning and Applications, 2005

Learning and Classifying Under Hard Budgets.
Proceedings of the Machine Learning: ECML 2005, 2005

Segmenting Brain Tumors with Conditional Random Fields and Support Vector Machines.
Proceedings of the Computer Vision for Biomedical Image Applications, 2005

Improving Protein Function Prediction Using the Hierarchical Structure of the Gene Ontology.
Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2005

Learning a Dynamic Classification Method to Detect Faces and Identify Facial Expression.
Proceedings of the Analysis and Modelling of Faces and Gestures, 2005

Goal-Directed Site-Independent Recommendations from Passive Observations.
Proceedings of the Proceedings, 2005

The Proteome Analyst Suite of Automated Function Prediction Tools.
Proceedings of the Proceedings, 2005

Discriminative Model Selection for Belief Net Structures.
Proceedings of the Proceedings, 2005

2004
Proteome Analyst: custom predictions with explanations in a web-based tool for high-throughput proteome annotations.
Nucleic Acids Research, 2004

Predicting subcellular localization of proteins using machine-learned classifiers.
Bioinformatics, 2004

Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields.
Proceedings of the 2004 International Symposium on Chinese Spoken Language Processing, 2004

Batch Reinforcement Learning with State Importance.
Proceedings of the Machine Learning: ECML 2004, 2004

The Budgeted Multi-armed Bandit Problem.
Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004

2003
An Effective Complete-Web Recommender System.
Proceedings of the Twelfth International World Wide Web Conference, 2003

Learning a Model of a Web User's Interests.
Proceedings of the User Modeling 2003, 2003

Predicting Web Information Content.
Proceedings of the Intelligent Techniques for Web Personalization, IJCAI 2003 Workshop, 2003

Use of Off-line Dynamic Programming for Efficient Image Interpretation.
Proceedings of the IJCAI-03, 2003

Lookahead Pathologies for Single Agent Search.
Proceedings of the IJCAI-03, 2003

Discriminative Parameter Learning of General Bayesian Network Classifiers.
Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2003), 2003

Towards Automated Creation of Image Interpretation Systems.
Proceedings of the AI 2003: Advances in Artificial Intelligence, 2003

2002
Learning cost-sensitive active classifiers.
Artif. Intell., 2002

Learning Bayesian networks from data: An information-theory based approach.
Artif. Intell., 2002

Performance of Lookahead Control Policies in the Face of Abstractions and Approximations.
Proceedings of the Abstraction, 2002

Structural Extension to Logistic Regression: Discriminative Parameter Learning of Belief Net Classifiers.
Proceedings of the Eighteenth National Conference on Artificial Intelligence and Fourteenth Conference on Innovative Applications of Artificial Intelligence, July 28, 2002

Optimal Depth-First Strategies for And-Or Trees.
Proceedings of the Eighteenth National Conference on Artificial Intelligence and Fourteenth Conference on Innovative Applications of Artificial Intelligence, July 28, 2002

2001
Efficient reasoning.
ACM Comput. Surv., 2001

Efficient Interpretation Policies.
Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, 2001

Efficient Car Recognition Policies.
Proceedings of the 2001 IEEE International Conference on Robotics and Automation, 2001

Learning Bayesian Belief Network Classifiers: Algorithms and System.
Proceedings of the Advances in Artificial Intelligence, 2001

2000
Model Selection Criteria for Learning Belief Nets: An Empirical Comparison.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

Predicting UNIX Command Lines: Adjusting to User Patterns.
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on on Innovative Applications of Artificial Intelligence, July 30, 2000

1999
The Complexity of Revising Logic Programs.
J. Log. Program., 1999

1997
The Relevance of Relevance (Editorial).
Artif. Intell., 1997

Knowing what doesn't Matter: Exploiting the Omission of Irrelevant Data.
Artif. Intell., 1997

Why Experimentation can be better than "Perfect Guidance".
Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997

1996
Learning to select useful landmarks.
IEEE Trans. Systems, Man, and Cybernetics, Part B, 1996

Probably Approximately Optimal Satisficing Strategies.
Artif. Intell., 1996

PALO: A Probabilistic Hill-Climbing Algorithm.
Artif. Intell., 1996

Learning Active Classifiers.
Proceedings of the Machine Learning, 1996

Exploiting the Omission of Irrelevant Data.
Proceedings of the Machine Learning, 1996

1995
Practical PAC Learning.
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 1995

The Complexity of Theory Revision.
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 1995

The Challenge of Revising an Impure Theory.
Proceedings of the Machine Learning, 1995

Sequential PAC Learning.
Proceedings of the Eigth Annual Conference on Computational Learning Theory, 1995

1993
D. B. Lenat and R. V. Guha, Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project.
Artif. Intell., 1993

1992
Learning Efficient Query Processing Strategies.
Proceedings of the Eleventh ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, 1992

Learning Useful Horn Approximations.
Proceedings of the 3rd International Conference on Principles of Knowledge Representation and Reasoning (KR'92). Cambridge, 1992

Learning an Optimally Accurate Representation System.
Proceedings of the Foundation of Knowledge Representation and Reasoning [the book grew out of an ECAI-92 workshop], 1992

A Statistical Approach to Solving the EBL Utility Problem.
Proceedings of the 10th National Conference on Artificial Intelligence, 1992

1991
Finding Optimal Derivation Strategies in Redundant Knowledge Bases.
Artif. Intell., 1991

Probably Approximately Optimal Derivation Strategies.
Proceedings of the 2nd International Conference on Principles of Knowledge Representation and Reasoning (KR'91). Cambridge, 1991

Measuring and Improving the Effectiveness of Representations.
Proceedings of the 12th International Joint Conference on Artificial Intelligence. Sydney, 1991

1990
On the Sample Complexity of Finding Good Search Strategies.
Proceedings of the Third Annual Workshop on Computational Learning Theory, 1990

1989
A Correction to the Algorithm in Reiter's Theory of Diagnosis.
Artif. Intell., 1989

Incorporating Redundant Learned Rules: A Preliminary Formal Analysis of EBL.
Proceedings of the 11th International Joint Conference on Artificial Intelligence. Detroit, 1989

Towards a Formal Analysis of EBL.
Proceedings of the Sixth International Workshop on Machine Learning (ML 1989), 1989

1988
A Review of Machine Learning at AAAI-87.
Machine Learning, 1988

Against the unjustified use of probabilities.
Computational Intelligence, 1988

Learning by Understanding Analogies.
Artif. Intell., 1988

1983
What's New? A Semantic Definition of Novelty.
Proceedings of the 8th International Joint Conference on Artificial Intelligence. Karlsruhe, 1983

1980
A Representation Language Language.
Proceedings of the 1st Annual National Conference on Artificial Intelligence, 1980


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