| 2024 | ICIS | Naive Algorithmic Collusion: When Do Bandit Learners Cooperate and When Do They Compete? | Connor Douglas, Foster J. Provost, Arun Sundarajan |
| 2020 | ICIS | Combining Observational and Experimental Data to Improve Large-Scale Decision-Making. | Carlos Fernndez-Lora, Foster J. Provost |
| 2020 | KDD | Data Science for the Real Estate Industry. | Ron Bekkerman, Vanja Josifovski, Foster J. Provost |
| 2019 | ICIS | Counterfactual Explanations for Data-Driven Decisions. | Carlos Fernandez, Foster J. Provost, Xintian Han |
| 2018 | KDD | Societal Impact of Data Science and Artificial Intelligence. | Foster J. Provost, James Hodson, Jeannette M. Wing, Qiang Yang, Jennifer Neville |
| 2016 | WSDM | The Predictive Power of Massive Data about our Fine-Grained Behavior. | Foster J. Provost |
| 2015 | KDD | Measuring Causal Impact of Online Actions via Natural Experiments: Application to Display Advertising. | Daniel N. Hill, Robert Moakler, Alan E. Hubbard, Vadim Tsemekhman, Foster J. Provost, Kiril Tsemekhman |
| 2014 | KDD | Scalable hands-free transfer learning for online advertising. | Brian Dalessandro, Daizhuo Chen, Troy Raeder, Claudia Perlich, Melinda Han Williams, Foster J. Provost |
| 2014 | KDD | Corporate residence fraud detection. | Enric Junqu de Fortuny, Marija Stankova, Julie Moeyersoms, Bart Minnaert, Foster J. Provost, David Martens |
| 2014 | KDD | Pleasing the advertising oracle: Probabilistic prediction from sampled, aggregated ground truth. | Melinda Han Williams, Claudia Perlich, Brian Dalessandro, Foster J. Provost |
| 2013 | KDD | Panel: a data scientist's guide to making money from start-ups. | Foster J. Provost, Geoffrey I. Webb |
| 2013 | KDD | Scalable supervised dimensionality reduction using clustering. | Troy Raeder, Claudia Perlich, Brian Dalessandro, Ori Stitelman, Foster J. Provost |
| 2013 | KDD | Using co-visitation networks for detecting large scale online display advertising exchange fraud. | Ori Stitelman, Claudia Perlich, Brian Dalessandro, Rod Hook, Troy Raeder, Foster J. Provost |
| 2012 | KDD | Bid optimizing and inventory scoring in targeted online advertising. | Claudia Perlich, Brian Dalessandro, Rod Hook, Ori Stitelman, Troy Raeder, Foster J. Provost |
| 2012 | KDD | Design principles of massive, robust prediction systems. | Troy Raeder, Ori Stitelman, Brian Dalessandro, Claudia Perlich, Foster J. Provost |
| 2011 | AAAI | Beat the Machine: Challenging Workers to Find the Unknown Unknowns. | Josh Attenberg, Panagiotis G. Ipeirotis, Foster J. Provost |
| 2011 | KDD | Online active inference and learning. | Josh Attenberg, Foster J. Provost |
| 2010 | HCOMP | Quality management on Amazon Mechanical Turk. | Panagiotis G. Ipeirotis, Foster J. Provost, Jing Wang |
| 2010 | KDD | Why label when you can search?: alternatives to active learning for applying human resources to build classification models under extreme class imbalance. | Josh Attenberg, Foster J. Provost |
| 2009 | KDD | Brand advertising, on-line audiences, and social media: invited talk. | Foster J. Provost |
| 2009 | KDD | Audience selection for on-line brand advertising: privacy-friendly social network targeting. | Foster J. Provost, Brian Dalessandro, Rod Hook, Xiaohan Zhang, Alan Murray |
| 2008 | KDD | Get another label? improving data quality and data mining using multiple, noisy labelers. | Victor S. Sheng, Foster J. Provost, Panagiotis G. Ipeirotis |
| 2006 | ICML | A Brief Survey of Machine Learning Methods for Classification in Networked Data and an Application to Suspicion Scoring. | Sofus Attila Macskassy, Foster J. Provost |
| 2005 | ICDM | An Expected Utility Approach to Active Feature-Value Acquisition. | Prem Melville, Foster J. Provost, Raymond J. Mooney |
| 2005 | ICML | ROC confidence bands: an empirical evaluation. | Sofus A. Macskassy, Foster J. Provost, Saharon Rosset |
| 2004 | ICDM | Active Feature-Value Acquisition for Classifier Induction. | Prem Melville, Maytal Saar-Tsechansky, Foster J. Provost, Raymond J. Mooney |
| 2003 | KDD | Aggregation-based feature invention and relational concept classes. | Claudia Perlich, Foster J. Provost |
| 2001 | IJCAI | Active Learning for Class Probability Estimation and Ranking. | Maytal Saar-Tsechansky, Foster J. Provost |
| 2001 | SIGIR | Intelligent Information Triage. | Sofus A. Macskassy, Haym Hirsh, Foster J. Provost, Ramesh Sankaranarayanan, Vasant Dhar |
| 1999 | KDD | Activity Monitoring: Noticing Interesting Changes in Behavior. | Tom Fawcett, Foster J. Provost |
| 1999 | KDD | Efficient Progressive Sampling. | Foster J. Provost, David D. Jensen, Tim Oates |
| 1998 | AAAI | Robust Classification Systems for Imprecise Environments. | Foster J. Provost, Tom Fawcett |
| 1998 | ICML | The Case against Accuracy Estimation for Comparing Induction Algorithms. | Foster J. Provost, Tom Fawcett, Ron Kohavi |
| 1997 | KDD | Increasing the Efficiency of Data Mining Algorithms with Breadth-First Marker Propagation. | John M. Aronis, Foster J. Provost |
| 1997 | KDD | Analysis and Visualization of Classifier Performance: Comparison under Imprecise Class and Cost Distributions. | Foster J. Provost, Tom Fawcett |
| 1997 | KDD | Scaling Up Inductive Algorithms: An Overview. | Foster J. Provost, Venkateswarlu Kolluri |
| 1996 | AAAI | Scaling Up: Distributed Machine Learning with Cooperation. | Foster J. Provost, Daniel N. Hennessy |
| 1996 | KDD | Exploiting Background Knowledge in Automated Discovery. | John M. Aronis, Foster J. Provost, Bruce G. Buchanan |
| 1996 | KDD | Combining Data Mining and Machine Learning for Effective User Profiling. | Tom Fawcett, Foster J. Provost |
| 1994 | ISMB | Distributed Machine Learning: Scaling Up with Coarse-grained Parallelism. | Foster J. Provost, Daniel N. Hennessy |
| 1994 | KDD | Efficiently Constructing Relational Features from Background Knowledge for Inductive Machine Learning. | John M. Aronis, Foster J. Provost |
| 1993 | AAAI | Iterative Weakening: Optimal and Near-Optimal Policies for the Selection of Search Bias. | Foster J. Provost |
| 1993 | ICML | Small Disjuncts in Action: Learning to Diagnose Errors in the Local Loop of the Telephone Network. | Andrea Pohoreckyj Danyluk, Foster J. Provost |
| 1992 | AAAI | Inductive Policy. | Foster J. Provost, Bruce G. Buchanan |
| 1992 | ICTAI | ClimBS: Searching the Bias Space. | Foster J. Provost |
| 1990 | ICTAI | RL4: a tool for knowledge-based induction. | Scott H. Clearwater, Foster J. Provost |