Foster J. Provost

Affiliations:
  • New York University, USA


According to our database1, Foster J. Provost authored at least 113 papers between 1990 and 2024.

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Bibliography

2024
Causal Fine-Tuning and Effect Calibration of Non-Causal Predictive Models.
CoRR, 2024

2023
A Comparison of Methods for Treatment Assignment with an Application to Playlist Generation.
Inf. Syst. Res., 2023

Who's Watching TV?
Inf. Syst. Res., 2023

The Impact of Cloaking Digital Footprints on User Privacy and Personalization.
CoRR, 2023

2022
Causal Classification: Treatment Effect Estimation vs. Outcome Prediction.
J. Mach. Learn. Res., 2022

2021
Node classification over bipartite graphs through projection.
Mach. Learn., 2021

Causal Decision Making and Causal Effect Estimation Are Not the Same... and Why It Matters.
CoRR, 2021

2020
In memory of Tom Fawcett.
Mach. Learn., 2020

A benchmarking study of classification techniques for behavioral data.
Int. J. Data Sci. Anal., 2020

Methods for Individual Treatment Assignment: An Application and Comparison for Playlist Generation.
CoRR, 2020

Explaining Data-Driven Decisions made by AI Systems: The Counterfactual Approach.
CoRR, 2020

A comparison of instance-level counterfactual explanation algorithms for behavioral and textual data: SEDC, LIME-C and SHAP-C.
Adv. Data Anal. Classif., 2020

Data Science for the Real Estate Industry.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Combining Observational and Experimental Data to Improve Large-Scale Decision-Making.
Proceedings of the 41st International Conference on Information Systems, 2020

2019
Unsupervised dimensionality reduction versus supervised regularization for classification from sparse data.
Data Min. Knowl. Discov., 2019

Counterfactual Explanation Algorithms for Behavioral and Textual Data.
CoRR, 2019

Deep Learning on Big, Sparse, Behavioral Data.
Big Data, 2019

Counterfactual Explanations for Data-Driven Decisions.
Proceedings of the 40th International Conference on Information Systems, 2019

2018
Wallenius Bayes.
Mach. Learn., 2018

Data-Driven Investment Strategies for Peer-to-Peer Lending: A Case Study for Teaching Data Science.
Big Data, 2018

Societal Impact of Data Science and Artificial Intelligence.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

2017
Cost-Effective Quality Assurance in Crowd Labeling.
Inf. Syst. Res., 2017

Big Data, Data Science, and Civil Rights.
CoRR, 2017

Enhancing Transparency and Control When Drawing Data-Driven Inferences About Individuals.
Big Data, 2017

2016
Mining Massive Fine-Grained Behavior Data to Improve Predictive Analytics.
MIS Q., 2016

Explaining Classification Models Built on High-Dimensional Sparse Data.
CoRR, 2016

The Predictive Power of Massive Data about our Fine-Grained Behavior.
Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, 2016

2015
Beat the Machine: Challenging Humans to Find a Predictive Model's "Unknown Unknowns".
ACM J. Data Inf. Qual., 2015

Finding Similar Mobile Consumers with a Privacy-Friendly Geosocial Design.
Inf. Syst. Res., 2015

Evaluating and Optimizing Online Advertising: Forget the Click, but There Are Good Proxies.
Big Data, 2015

Measuring Causal Impact of Online Actions via Natural Experiments: Application to Display Advertising.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Iteratively refining SVMs using priors.
Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

2014
Machine learning for targeted display advertising: transfer learning in action.
Mach. Learn., 2014

Explaining Data-Driven Document Classifications.
MIS Q., 2014

Repeated labeling using multiple noisy labelers.
Data Min. Knowl. Discov., 2014

A Data Scientist's Guide to Start-Ups.
Big Data, 2014

Authors' Response to Gong's, "Comment on Data Science and its Relationship to Big Data and Data-Driven Decision Making".
Big Data, 2014

ACM SIGKDD 2014 to be Held August 24-27 in Manhattan.
Big Data, 2014

Pleasing the advertising oracle: Probabilistic prediction from sampled, aggregated ground truth.
Proceedings of the Eighth International Workshop on Data Mining for Online Advertising, 2014

Corporate residence fraud detection.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Scalable hands-free transfer learning for online advertising.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

2013
Research Commentary - Information in Digital, Economic, and Social Networks.
Inf. Syst. Res., 2013

Data Science and its Relationship to Big Data and Data-Driven Decision Making.
Big Data, 2013

Predictive Modeling With Big Data: <i>Is Bigger Really Better</i>?
Big Data, 2013

Using co-visitation networks for detecting large scale online display advertising exchange fraud.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Scalable supervised dimensionality reduction using clustering.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Panel: a data scientist's guide to making money from start-ups.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Hyperlocal: inferring location of IP addresses in real-time bid requests for mobile ads.
Proceedings of the 6th ACM SIGSPATIAL International Workshop on Location-Based Social Networks, 2013

2012
Design principles of massive, robust prediction systems.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Bid optimizing and inventory scoring in targeted online advertising.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Causally motivated attribution for online advertising.
Proceedings of the Sixth International Workshop on Data Mining for Online Advertising and Internet Economy, 2012

2011
Online active inference and learning.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Beat the Machine: Challenging Workers to Find the Unknown Unknowns.
Proceedings of the Human Computation, 2011

2010
Inactive learning?: difficulties employing active learning in practice.
SIGKDD Explor., 2010

A Unified Approach to Active Dual Supervision for Labeling Features and Examples.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

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, 2010

Quality management on Amazon Mechanical Turk.
Proceedings of the ACM SIGKDD Workshop on Human Computation, 2010

2009
Active Feature-Value Acquisition.
Manag. Sci., 2009

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, 2009

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, 2009

2008
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, 2008

2007
Handling Missing Values when Applying Classification Models.
J. Mach. Learn. Res., 2007

Classification in Networked Data: A Toolkit and a Univariate Case Study.
J. Mach. Learn. Res., 2007

Decision-Centric Active Learning of Binary-Outcome Models.
Inf. Syst. Res., 2007

Modeling complex networks for electronic commerce.
Proceedings of the Proceedings 8th ACM Conference on Electronic Commerce (EC-2007), 2007

Learning and Inference in Massive Social Networks.
Proceedings of the Mining and Learning with Graphs, 2007

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

2006
Distribution-based aggregation for relational learning with identifier attributes.
Mach. Learn., 2006

A Brief Survey of Machine Learning Methods for Classification in Networked Data and an Application to Suspicion Scoring.
Proceedings of the Statistical Network Analysis: Models, Issues, and New Directions, 2006

2005
Toward Intelligent Assistance for a Data Mining Process: An Ontology-Based Approach for Cost-Sensitive Classification.
IEEE Trans. Knowl. Data Eng., 2005

ROC confidence bands: an empirical evaluation.
Proceedings of the Machine Learning, 2005

An Expected Utility Approach to Active Feature-Value Acquisition.
Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), 2005

2004
Active Sampling for Class Probability Estimation and Ranking.
Mach. Learn., 2004

Confidence Bands for ROC Curves: Methods and an Empirical Study.
Proceedings of the ROC Analysis in Artificial Intelligence, 1st International Workshop, 2004

Active Feature-Value Acquisition for Classifier Induction.
Proceedings of the 4th IEEE International Conference on Data Mining (ICDM 2004), 2004

Knowledge Discovery Using Concept-Class Taxonomies.
Proceedings of the AI 2004: Advances in Artificial Intelligence, 2004

2003
Predicting citation rates for physics papers: constructing features for an ordered probit model.
SIGKDD Explor., 2003

The myth of the double-blind review?: author identification using only citations.
SIGKDD Explor., 2003

Tree Induction for Probability-Based Ranking.
Mach. Learn., 2003

Tree Induction vs. Logistic Regression: A Learning-Curve Analysis.
J. Mach. Learn. Res., 2003

Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction.
J. Artif. Intell. Res., 2003

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, 2003

2001
Robust Classification for Imprecise Environments.
Mach. Learn., 2001

Applications of Data Mining to Electronic Commerce.
Data Min. Knowl. Discov., 2001

Intelligent Information Triage.
Proceedings of the SIGIR 2001: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2001

Active Learning for Class Probability Estimation and Ranking.
Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, 2001

2000
Discovering Interesting Patterns for Investment Decision Making with GLOWER - A Genetic Learner Overlaid with Entropy Reduction.
Data Min. Knowl. Discov., 2000

1999
Problem Definition, Data Cleaning, and Evaluation: A Classifier Learning Case Study.
Informatica (Slovenia), 1999

A Survey of Methods for Scaling Up Inductive Algorithms.
Data Min. Knowl. Discov., 1999

Efficient Progressive Sampling.
Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1999

Activity Monitoring: Noticing Interesting Changes in Behavior.
Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1999

1998
Guest Editors' Introduction: On Applied Research in Machine Learning.
Mach. Learn., 1998

AI Approaches to Fraud Detection and Risk Management.
AI Mag., 1998

The Case against Accuracy Estimation for Comparing Induction Algorithms.
Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998

Robust Classification Systems for Imprecise Environments.
Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, 1998

1997
Adaptive Fraud Detection.
Data Min. Knowl. Discov., 1997

Scaling Up Inductive Algorithms: An Overview.
Proceedings of the Third International Conference on Knowledge Discovery and Data Mining (KDD-97), 1997

Analysis and Visualization of Classifier Performance: Comparison under Imprecise Class and Cost Distributions.
Proceedings of the Third International Conference on Knowledge Discovery and Data Mining (KDD-97), 1997

Increasing the Efficiency of Data Mining Algorithms with Breadth-First Marker Propagation.
Proceedings of the Third International Conference on Knowledge Discovery and Data Mining (KDD-97), 1997

1996
Scaling Up Inductive Learning with Massive Parallelism.
Mach. Learn., 1996

Combining Data Mining and Machine Learning for Effective User Profiling.
Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), 1996

Exploiting Background Knowledge in Automated Discovery.
Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), 1996

Scaling Up: Distributed Machine Learning with Cooperation.
Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 1996

1995
Inductive Policy: The Pragmatics of Bias Selection.
Mach. Learn., 1995

1994
Efficiently Constructing Relational Features from Background Knowledge for Inductive Machine Learning.
Proceedings of the Knowledge Discovery in Databases: Papers from the 1994 AAAI Workshop, 1994

Distributed Machine Learning: Scaling Up with Coarse-grained Parallelism.
Proceedings of the Second International Conference on Intelligent Systems for Molecular Biology, 1994

1993
Small Disjuncts in Action: Learning to Diagnose Errors in the Local Loop of the Telephone Network.
Proceedings of the Machine Learning, 1993

Iterative Weakening: Optimal and Near-Optimal Policies for the Selection of Search Bias.
Proceedings of the 11th National Conference on Artificial Intelligence. Washington, 1993

1992
A Distributed Algorithm for Embedding Trees in Hypercubes with Modifications for Run-Time Fault Tolerance.
J. Parallel Distributed Comput., 1992

ClimBS: Searching the Bias Space.
Proceedings of the Fourth International Conference on Tools with Artificial Intelligence, 1992

Inductive Strengthening: the Effects of a Simple Heuristic for Restricting Hypothesis Space Search.
Proceedings of the Analogical and Inductive Inference, 1992

Inductive Policy.
Proceedings of the 10th National Conference on Artificial Intelligence, 1992

1990
RL4: a tool for knowledge-based induction.
Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence, 1990


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