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    First name: Foster J.
    Last name: Provost
    DBLP: p/FosterJProvost
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    Below you find the publications which have been written by this author.

    Show item 1 to 73 of 73  
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    Journal article
    Panagiotis G. Ipeirotis, Foster J. Provost, Victor S. Sheng, Jing Wang.
    Repeated labeling using multiple noisy labelers.
    Data Min. Knowl. Discov. 2014, Volume 28 (0) 2014
    Journal article
    Claudia Perlich, Brian Dalessandro, Troy Raeder, Ori Stitelman, Foster J. Provost.
    Machine learning for targeted display advertising: transfer learning in action.
    Machine Learning 2014, Volume 95 (0) 2014
    Conference paper
    Enric Junqué de Fortuny, Marija Stankova, Julie Moeyersoms, Bart Minnaert, Foster J. Provost, David Martens.
    Corporate residence fraud detection.
    The 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '14, New York, NY, USA - August 24 - 27, 2014 2014 (0) 2014
    Conference paper
    Melinda Han Williams, Claudia Perlich, Brian Dalessandro, Foster J. Provost.
    Pleasing the advertising oracle: Probabilistic prediction from sampled, aggregated ground truth.
    Proceedings of the Eighth International Workshop on Data Mining for Online Advertising, ADKDD 2014, August 24, 2014, New York City, New York, USA 2014 (0) 2014
    Conference paper
    Brian Dalessandro, Daizhuo Chen, Troy Raeder, Claudia Perlich, Melinda Han Williams, Foster J. Provost.
    Scalable hands-free transfer learning for online advertising.
    The 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '14, New York, NY, USA - August 24 - 27, 2014 2014 (0) 2014
    Conference paper
    Ori Stitelman, Claudia Perlich, Brian Dalessandro, Rod Hook, Troy Raeder, Foster J. Provost.
    Using co-visitation networks for detecting large scale online display advertising exchange fraud.
    The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013, Chicago, IL, USA, August 11-14, 2013 2013 (0) 2013
    Conference paper
    Foster J. Provost, Geoffrey I. Webb.
    Panel: a data scientist's guide to making money from start-ups.
    The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013, Chicago, IL, USA, August 11-14, 2013 2013 (0) 2013
    Conference paper
    Troy Raeder, Claudia Perlich, Brian Dalessandro, Ori Stitelman, Foster J. Provost.
    Scalable supervised dimensionality reduction using clustering.
    The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013, Chicago, IL, USA, August 11-14, 2013 2013 (0) 2013
    Conference paper
    Arun Sundararajan, Foster J. Provost, Gal Oestreicher-Singer, Sinan Aral.
    Research Commentary - Information in Digital, Economic, and Social Networks.
    Information Systems Research 2013, Volume 24 (0) 2013
    Conference paper
    Claudia Perlich, Brian Dalessandro, Rod Hook, Ori Stitelman, Troy Raeder, Foster J. Provost.
    Bid optimizing and inventory scoring in targeted online advertising.
    The 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '12, Beijing, China, August 12-16, 2012 2012 (0) 2012
    Conference paper
    Troy Raeder, Ori Stitelman, Brian Dalessandro, Claudia Perlich, Foster J. Provost.
    Design principles of massive, robust prediction systems.
    The 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '12, Beijing, China, August 12-16, 2012 2012 (0) 2012
    Journal article
    Foster J. Provost, Gary M. Weiss.
    Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction
    CoRR 2011, Volume 0 (0) 2011
    Conference paper
    Josh Attenberg, Foster J. Provost.
    Online active inference and learning.
    Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Diego, CA, USA, August 21-24, 2011 2011 (0) 2011
    Conference paper
    Josh Attenberg, Panagiotis G. Ipeirotis, Foster J. Provost.
    Beat the Machine: Challenging Workers to Find the Unknown Unknowns.
    Human Computation, Papers from the 2011 AAAI Workshop, San Francisco, California, USA, August 8, 2011 2011 (0) 2011
    Conference paper
    Josh Attenberg, Foster J. Provost.
    Why label when you can search?: alternatives to active learning for applying human resources to build classification models under extreme class imbalance.
    Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, July 25-28, 2010 2010 (0) 2010
    Conference paper
    Josh Attenberg, Prem Melville, Foster J. Provost.
    A Unified Approach to Active Dual Supervision for Labeling Features and Examples.
    Machine Learning and Knowledge Discovery in Databases, European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010, Proceedings, Part I 2010 (0) 2010
    Conference paper
    Josh Attenberg, Foster J. Provost.
    Inactive learning?: difficulties employing active learning in practice.
    SIGKDD Explorations 2010, Volume 12 (0) 2010
    Conference paper
    Foster J. Provost, Brian Dalessandro, Rod Hook, Xiaohan Zhang, Alan Murray.
    Audience selection for on-line brand advertising: privacy-friendly social network targeting.
    Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28 - July 1, 2009 2009 (0) 2009
    Conference paper
    Foster J. Provost.
    Brand advertising, on-line audiences, and social media: invited talk.
    Proceedings of the 3rd ACM SIGKDD Workshop on Data Mining and Audience Intelligence for Advertising, Paris, France, June 28, 2009 2009 (0) 2009
    Journal article
    Maytal Saar-Tsechansky, Prem Melville, Foster J. Provost.
    Active Feature-Value Acquisition.
    Management Science 2009, Volume 55 (0) 2009
    Conference paper
    Victor S. Sheng, Foster J. Provost, Panagiotis G. Ipeirotis.
    Get another label? improving data quality and data mining using multiple, noisy labelers.
    Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Las Vegas, Nevada, USA, August 24-27, 2008 2008 (0) 2008
    Conference paper
    Maytal Saar-Tsechansky, Foster J. Provost.
    Handling Missing Values when Applying Classification Models.
    Journal of Machine Learning Research 2007, Volume 8 (0) 2007
    Conference paper
    Sofus A. Macskassy, Foster J. Provost.
    Classification in Networked Data: A Toolkit and a Univariate Case Study.
    Journal of Machine Learning Research 2007, Volume 8 (0) 2007
    Conference paper
    Foster J. Provost, Prem Melville, Maytal Saar-Tsechansky.
    Data acquisition and cost-effective predictive modeling: targeting offers for electronic commerce.
    Proceedings of the 9th International Conference on Electronic Commerce: The Wireless World of Electronic Commerce, 2007, University of Minnesota, Minneapolis, MN, USA, August 19-22, 2007 2007 (0) 2007
    Conference paper
    Foster J. Provost, Arun Sundararajan.
    Modeling complex networks for electronic commerce.
    Proceedings 8th ACM Conference on Electronic Commerce (EC-2007), San Diego, California, USA, June 11-15, 2007 2007 (0) 2007
    Conference paper
    Shawndra Hill, Foster J. Provost, Chris Volinsky.
    Learning and Inference in Massive Social Networks.
    Mining and Learning with Graphs, MLG 2007, Firence, Italy, August 1-3, 2007, Proceedings 2007 (0) 2007
    Conference paper
    Maytal Saar-Tsechansky, Foster J. Provost.
    Decision-Centric Active Learning of Binary-Outcome Models.
    Information Systems Research 2007, Volume 18 (0) 2007
    Conference paper
    Claudia Perlich, Foster J. Provost.
    Distribution-based aggregation for relational learning with identifier attributes.
    Machine Learning 2006, Volume 62 (0) 2006
    Conference paper
    Prem Melville, Foster J. Provost, Raymond J. Mooney.
    An Expected Utility Approach to Active Feature-Value Acquisition.
    Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), 27-30 November 2005, Houston, Texas, USA 2005 (0) 2005
    Conference paper
    Sofus A. Macskassy, Foster J. Provost, Saharon Rosset.
    ROC confidence bands: an empirical evaluation.
    Machine Learning, Proceedings of the Twenty-Second International Conference (ICML 2005), Bonn, Germany, August 7-11, 2005 2005 (0) 2005
    Conference paper
    Abraham Bernstein, Foster J. Provost, Shawndra Hill.
    Toward Intelligent Assistance for a Data Mining Process: An Ontology-Based Approach for Cost-Sensitive Classification.
    IEEE Trans. Knowl. Data Eng. 2005, Volume 17 (0) 2005
    Conference paper
    Venkateswarlu Kolluri, Foster J. Provost, Bruce G. Buchanan, Douglas Metzler.
    Knowledge Discovery Using Concept-Class Taxonomies.
    AI 2004: Advances in Artificial Intelligence, 17th Australian Joint Conference on Artificial Intelligence, Cairns, Australia, December 4-6, 2004, Proceedings 2004 (0) 2004
    Conference paper
    Prem Melville, Maytal Saar-Tsechansky, Foster J. Provost, Raymond J. Mooney.
    Active Feature-Value Acquisition for Classifier Induction.
    Proceedings of the 4th IEEE International Conference on Data Mining (ICDM 2004), 1-4 November 2004, Brighton, UK 2004 (0) 2004
    Conference paper
    Sofus A. Macskassy, Foster J. Provost.
    Confidence Bands for ROC Curves: Methods and an Empirical Study.
    ROC Analysis in Artificial Intelligence, 1st International Workshop, ROCAI-2004, Valencia, Spain, August 22, 2004 2004 (0) 2004
    Conference paper
    Maytal Saar-Tsechansky, Foster J. Provost.
    Active Sampling for Class Probability Estimation and Ranking.
    Machine Learning 2004, Volume 54 (0) 2004
    Conference paper
    Claudia Perlich, Foster J. Provost.
    Aggregation-based feature invention and relational concept classes.
    Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 24 - 27, 2003 2003 (0) 2003
    Conference paper
    Claudia Perlich, Foster J. Provost, Jeffrey S. Simonoff.
    Tree Induction vs. Logistic Regression: A Learning-Curve Analysis.
    Journal of Machine Learning Research 2003, Volume 4 (0) 2003
    Conference paper
    Foster J. Provost, Pedro Domingos.
    Tree Induction for Probability-Based Ranking.
    Machine Learning 2003, Volume 52 (0) 2003
    Conference paper
    Shawndra Hill, Foster J. Provost.
    The myth of the double-blind review?: author identification using only citations.
    SIGKDD Explorations 2003, Volume 5 (0) 2003
    Conference paper
    Claudia Perlich, Foster J. Provost, Sofus A. Macskassy.
    Predicting citation rates for physics papers: constructing features for an ordered probit model.
    SIGKDD Explorations 2003, Volume 5 (0) 2003
    Conference paper
    Gary M. Weiss, Foster J. Provost.
    Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction.
    J. Artif. Intell. Res. (JAIR) 2003, Volume 19 (0) 2003
    Conference paper
    Maytal Saar-Tsechansky, Foster J. Provost.
    Active Learning for Class Probability Estimation and Ranking.
    Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, IJCAI 2001, Seattle, Washington, USA, August 4-10, 2001 2001 (0) 2001
    Conference paper
    Sofus A. Macskassy, Haym Hirsh, Foster J. Provost, Ramesh Sankaranarayanan, Vasant Dhar.
    Intelligent Information Triage.
    SIGIR 2001: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, September 9-13, 2001, New Orleans, Louisiana, USA 2001 (0) 2001
    Conference paper
    Ron Kohavi, Foster J. Provost.
    Applications of Data Mining to Electronic Commerce.
    Data Min. Knowl. Discov. 2001, Volume 5 (0) 2001
    Conference paper
    Foster J. Provost, Tom Fawcett.
    Robust Classification for Imprecise Environments.
    Machine Learning 2001, Volume 42 (0) 2001
    Conference paper
    Foster J. Provost, Tom Fawcett.
    Robust Classification for Imprecise Environments
    CoRR 2000, Volume 0 (0) 2000
    Conference paper
    Ron Kohavi, Foster J. Provost.
    Applications of Data Mining to Electronic Commerce
    CoRR 2000, Volume 0 (0) 2000
    Conference paper
    Vasant Dhar, Dashin Chou, Foster J. Provost.
    Discovering Interesting Patterns for Investment Decision Making with GLOWER - A Genetic Learner Overlaid with Entropy Reduction.
    Data Min. Knowl. Discov. 2000, Volume 4 (0) 2000
    Conference paper
    Tom Fawcett, Foster J. Provost.
    Activity Monitoring: Noticing Interesting Changes in Behavior.
    KDD 1999 (0) 1999
    Conference paper
    Foster J. Provost, David Jensen, Tim Oates.
    Efficient Progressive Sampling.
    KDD 1999 (0) 1999
    Conference paper
    Foster J. Provost, Venkateswarlu Kolluri.
    A Survey of Methods for Scaling Up Inductive Algorithms.
    Data Min. Knowl. Discov. 1999, Volume 3 (0) 1999
    Conference paper
    Foster J. Provost, Andrea Pohoreckyj Danyluk.
    Problem Definition, Data Cleaning, and Evaluation: A Classifier Learning Case Study.
    Informatica (Slovenia) 1999, Volume 23 (0) 1999
    Conference paper
    Foster J. Provost, Tom Fawcett.
    Robust Classification Systems for Imprecise Environments.
    AAAI/IAAI 1998 (0) 1998
    Conference paper
    Foster J. Provost, Tom Fawcett, Ron Kohavi.
    The Case against Accuracy Estimation for Comparing Induction Algorithms.
    Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), Madison, Wisconsin, USA, July 24-27, 1998 1998 (0) 1998
    Conference paper
    Tom Fawcett, Ira J. Haimowitz, Foster J. Provost, Salvatore J. Stolfo.
    AI Approaches to Fraud Detection and Risk Management.
    AI Magazine 1998, Volume 19 (0) 1998
    Conference paper
    Foster J. Provost, Ron Kohavi.
    Guest Editors' Introduction: On Applied Research in Machine Learning.
    Machine Learning 1998, Volume 30 (0) 1998
    Conference paper
    John M. Aronis, Foster J. Provost.
    Increasing the Efficiency of Data Mining Algorithms with Breadth-First Marker Propagation.
    KDD 1997 (0) 1997
    Conference paper
    Foster J. Provost, Tom Fawcett.
    Analysis and Visualization of Classifier Performance: Comparison under Imprecise Class and Cost Distributions.
    KDD 1997 (0) 1997
    Conference paper
    Foster J. Provost, Venkateswarlu Kolluri.
    Scaling Up Inductive Algorithms: An Overview.
    KDD 1997 (0) 1997
    Conference paper
    Tom Fawcett, Foster J. Provost.
    Adaptive Fraud Detection.
    Data Min. Knowl. Discov. 1997, Volume 1 (0) 1997
    Conference paper
    Foster J. Provost, Daniel N. Hennessy.
    Scaling Up: Distributed Machine Learning with Cooperation.
    AAAI/IAAI, Vol. 1 1996 (0) 1996
    Conference paper
    John M. Aronis, Foster J. Provost, Bruce G. Buchanan.
    Exploiting Background Knowledge in Automated Discovery.
    KDD 1996 (0) 1996
    Conference paper
    Tom Fawcett, Foster J. Provost.
    Combining Data Mining and Machine Learning for Effective User Profiling.
    KDD 1996 (0) 1996
    Conference paper
    Foster J. Provost, John M. Aronis.
    Scaling Up Inductive Learning with Massive Parallelism.
    Machine Learning 1996, Volume 23 (0) 1996
    Conference paper
    Foster J. Provost, Bruce G. Buchanan.
    Inductive Policy: The Pragmatics of Bias Selection.
    Machine Learning 1995, Volume 20 (0) 1995
    Conference paper
    Foster J. Provost, Daniel N. Hennessy.
    Distributed Machine Learning: Scaling Up with Coarse-grained Parallelism.
    Proceedings of the Second International Conference on Intelligent Systems for Molecular Biology, August 14-17, 1994, Stanford University, Stanford, California, USA 1994 (0) 1994
    Conference paper
    John M. Aronis, Foster J. Provost.
    Efficiently Constructing Relational Features from Background Knowledge for Inductive Machine Learning.
    KDD Workshop 1994 (0) 1994
    Conference paper
    Foster J. Provost.
    Iterative Weakening: Optimal and Near-Optimal Policies for the Selection of Search Bias.
    AAAI 1993 (0) 1993
    Conference paper
    Andrea Pohoreckyj Danyluk, Foster J. Provost.
    Small Disjuncts in Action: Learning to Diagnose Errors in the Local Loop of the Telephone Network.
    ICML 1993 (0) 1993
    Conference paper
    Foster J. Provost, Bruce G. Buchanan.
    Inductive Policy.
    AAAI 1992 (0) 1992
    Conference paper
    Foster J. Provost, Bruce G. Buchanan.
    Inductive Strengthening: the Effects of a Simple Heuristic for Restricting Hypothesis Space Search.
    Analogical and Inductive Inference, International Workshop AII '92, Dagstuhl Castle, Germany, October 5-9, 1992, Proceedings 1992 (0) 1992
    Conference paper
    Foster J. Provost.
    ClimBS: Searching the Bias Space.
    ICTAI 1992 (0) 1992
    Conference paper
    Foster J. Provost, Rami G. Melhem.
    A Distributed Algorithm for Embedding Trees in Hypercubes with Modifications for Run-Time Fault Tolerance.
    J. Parallel Distrib. Comput. 1992, Volume 14 (0) 1992
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