Foster Provost
- Computer Science Applications top 0.1%
- Artificial Intelligence top 0.05%
- Imbalanced Data Classification Techniques 42
- Machine Learning and Data Classification 41
- Machine Learning and Algorithms 29
- Anomaly Detection Techniques and Applications 13
- Bayesian Modeling and Causal Inference 12
- Information Systems top 0.1%
- Data Mining Algorithms and Applications 38
- Management Information Systems top 0.5%
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- Complex Network Analysis Techniques 16
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- Consumer Market Behavior and Pricing 15
- Co-authors
- Tom FawcettPanagiotis G. IpeirotisGary M. WeissRon KohaviVictor S. ShengJing WangMaytal Saar‐TsechanskySofus A. Macskassy
- Partner nations
- United StatesSwitzerlandFrance
In The Last Decade
Foster Provost
166 papers receiving 11.0k citations
Hit Papers
Peers
Comparison fields: 5 of 215
- Computer Science Applications 1.4k
- Artificial Intelligence 7.0k
- Information Systems 2.8k
- Management Science and Operations Research 1.5k
- Management Information Systems 777
Countries citing papers authored by Foster Provost
This map shows the geographic impact of Foster Provost's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Foster Provost with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Foster Provost more than expected).
Fields of papers citing papers by Foster Provost
This network shows the impact of papers produced by Foster Provost. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Foster Provost. The network helps show where Foster Provost may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Foster Provost, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | Counterfactual Explanations for Data-Driven Decisions | 2019 | 8 |
| 3 | Data science for business | 2013 | 45 |
| 4 | Explaining Data-Driven Document Classifications | 2013 | 8 |
| 5 | Evaluating and Optimizing Online Advertising: Forget the click, but\nthere are good proxies | 2012 | 20 |
| 6 | Explaining Documents' Classifications | 2011 | 2 |
| 7 | Pseudo-social network targeting from consumer transaction data | 2011 | 18 |
| 8 | Proceedings of the First Workshop on Social Media Analytics | 2010 | 13 |
| 9 | Get Another Label? Improving Data Quality and Data Mining Using Multiple, Noisy Labelers | 2008 | 58 |
| 10 | 2007 | 294 | |
| 11 | Handling Missing Values when Applying Classification Models | 2007 | 204 |
| 12 | ROC Confidence Bands: An Empirical Study | 2005 | 1 |
| 13 | Classification in Networked Data: a Toolkit and a Univariate Case Study | 2004 | 9 |
| 14 | Intelligent Assistance for the Data Mining Process: An Ontology-based Approach | 2002 | 18 |
| 15 | Tree Induction Vs. Logistic Regression: a Learning-Curve Analysis | 2001 | 114 |
| 16 | Variance-based Active Learning | 2000 | 1 |
| 17 | Robust classification systems for imprecise environments | 1998 | 88 |
| 18 | Analysis and visualization of classifier performance: comparison under imprecise class and cost distributions | 1997 | 490 |
| 19 | Scaling up inductive algorithms: an overview | 1997 | 12 |
| 20 | Inductive policy | 1992 | 14 |
About Foster Provost
Foster Provost is a scholar working on Artificial Intelligence, Information Systems and Management Science and Operations Research, having authored 172 papers that have together received 12.1k indexed citations. Recurring topics across this work include Imbalanced Data Classification Techniques (42 papers), Machine Learning and Data Classification (41 papers), Data Mining Algorithms and Applications (38 papers), Machine Learning and Algorithms (29 papers), Complex Network Analysis Techniques (16 papers), Consumer Market Behavior and Pricing (15 papers), Anomaly Detection Techniques and Applications (13 papers) and Bayesian Modeling and Causal Inference (12 papers). The work is most often cited by research in Computer Science Applications (1.4k citations), Artificial Intelligence (7.0k citations) and Information Systems (2.8k citations). Foster Provost has collaborated with scholars based in United States, Switzerland and France. Frequent co-authors include Tom Fawcett, Panagiotis G. Ipeirotis, Gary M. Weiss, Ron Kohavi, Victor S. Sheng, Jing Wang, Maytal Saar‐Tsechansky, Sofus A. Macskassy, Claudia Perlich and Pedro Domingos. Their work appears in journals such as Machine Learning, Big Data, Information Systems Research, Data Mining and Knowledge Discovery and MIS Quarterly.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.