| Hits ?▲ |
Authors |
Title |
Venue |
Year |
Link |
Author keywords |
| 1 | Foster J. Provost, Gary M. Weiss |
Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction  |
CoRR  |
2011 |
DBLP BibTeX RDF |
|
| 1 | Josh Attenberg, Panagiotis G. Ipeirotis, Foster J. Provost |
Beat the Machine: Challenging Workers to Find the Unknown Unknowns. |
Human Computation |
2011 |
DBLP BibTeX RDF |
|
| 1 | Josh Attenberg, Foster J. Provost |
Online active inference and learning. |
KDD |
2011 |
DBLP DOI BibTeX RDF |
|
| 1 | Josh Attenberg, Foster J. Provost |
Inactive learning?: difficulties employing active learning in practice. |
SIGKDD Explorations |
2010 |
DBLP DOI BibTeX RDF |
|
| 1 | Josh Attenberg, Prem Melville, Foster J. Provost |
A Unified Approach to Active Dual Supervision for Labeling Features and Examples. |
ECML/PKDD |
2010 |
DBLP DOI BibTeX RDF |
|
| 1 | 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. |
KDD |
2010 |
DBLP DOI BibTeX RDF |
micro-outsourcing, on-line advertising, machine learning, active learning, human resources, class imbalance |
| 1 | Maytal Saar-Tsechansky, Prem Melville, Foster J. Provost |
Active Feature-Value Acquisition. |
Management Science |
2009 |
DBLP DOI BibTeX RDF |
|
| 1 | Foster J. Provost |
Brand advertising, on-line audiences, and social media: invited talk. |
KDD Workshop on Data Mining and Audience Intelligence for Advertising |
2009 |
DBLP DOI BibTeX RDF |
|
| 1 | Paul N. Bennett, Raman Chandrasekar, Max Chickering, Panagiotis G. Ipeirotis, Edith Law, Anton Mityagin, Foster J. Provost, Luis von Ahn (eds.) |
Proceedings of the ACM SIGKDD Workshop on Human Computation, Paris, France, June 28, 2009 |
KDD Workshop on Human Computation |
2009 |
DBLP BibTeX RDF |
|
| 1 | Foster J. Provost, Brian Dalessandro, Rod Hook, Xiaohan Zhang, Alan Murray |
Audience selection for on-line brand advertising: privacy-friendly social network targeting. |
KDD |
2009 |
DBLP DOI BibTeX RDF |
on-line advertising, privacy, social networks, predictive modeling, user-generated content |
| 1 | Victor S. Sheng, Foster J. Provost, Panagiotis G. Ipeirotis |
Get another label? improving data quality and data mining using multiple, noisy labelers. |
KDD |
2008 |
DBLP DOI BibTeX RDF |
data preprocessing, data selection |
| 1 | Maytal Saar-Tsechansky, Foster J. Provost |
Decision-Centric Active Learning of Binary-Outcome Models. |
Information Systems Research |
2007 |
DBLP DOI BibTeX RDF |
|
| 1 | Maytal Saar-Tsechansky, Foster J. Provost |
Handling Missing Values when Applying Classification Models. |
Journal of Machine Learning Research |
2007 |
DBLP BibTeX RDF |
|
| 1 | Sofus A. Macskassy, Foster J. Provost |
Classification in Networked Data: A Toolkit and a Univariate Case Study. |
Journal of Machine Learning Research |
2007 |
DBLP BibTeX RDF |
|
| 1 | Foster J. Provost, Arun Sundararajan |
Modeling complex networks for electronic commerce. |
ACM Conference on Electronic Commerce |
2007 |
DBLP DOI BibTeX RDF |
network seeding, complex network, diffusion, random graph, small-world, network effects, collective inference |
| 1 | Foster J. Provost, Prem Melville, Maytal Saar-Tsechansky |
Data acquisition and cost-effective predictive modeling: targeting offers for electronic commerce. |
ICEC |
2007 |
DBLP DOI BibTeX RDF |
active feature-value acquisition, active information acquisition, electronic commerce, active learning, supervised learning |
| 1 | Shawndra Hill, Foster J. Provost, Chris Volinsky |
Learning and Inference in Massive Social Networks. |
MLG |
2007 |
DBLP BibTeX RDF |
|
| 1 | Claudia Perlich, Foster J. Provost |
Distribution-based aggregation for relational learning with identifier attributes. |
Machine Learning |
2006 |
DBLP DOI BibTeX RDF |
networks, aggregation, relational learning, identifiers |
| 1 | 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 |
DBLP DOI BibTeX RDF |
metalearning, data mining, machine learning, knowledge discovery, Cost-sensitive learning, intelligent assistants, knowledge discovery process, data mining process |
| 1 | Prem Melville, Foster J. Provost, Raymond J. Mooney |
An Expected Utility Approach to Active Feature-Value Acquisition. |
ICDM |
2005 |
DBLP DOI BibTeX RDF |
|
| 1 | Sofus A. Macskassy, Foster J. Provost, Saharon Rosset |
ROC confidence bands: an empirical evaluation. |
ICML |
2005 |
DBLP DOI BibTeX RDF |
|
| 1 | Maytal Saar-Tsechansky, Foster J. Provost |
Active Sampling for Class Probability Estimation and Ranking. |
Machine Learning |
2004 |
DBLP DOI BibTeX RDF |
class probability estimation, uncertainty sampling, decision trees, ranking, active learning, supervised learning, cost-sensitive learning, selective sampling |
| 1 | Prem Melville, Maytal Saar-Tsechansky, Foster J. Provost, Raymond J. Mooney |
Active Feature-Value Acquisition for Classifier Induction. |
ICDM |
2004 |
DBLP DOI BibTeX RDF |
|
| 1 | Venkateswarlu Kolluri, Foster J. Provost, Bruce G. Buchanan, Douglas Metzler |
Knowledge Discovery Using Concept-Class Taxonomies. |
Australian Conference on Artificial Intelligence |
2004 |
DBLP DOI BibTeX RDF |
|
| 1 | Sofus A. Macskassy, Foster J. Provost |
Confidence Bands for ROC Curves: Methods and an Empirical Study. |
ROCAI |
2004 |
DBLP BibTeX RDF |
|
| 1 | Claudia Perlich, Foster J. Provost, Jeffrey S. Simonoff |
Tree Induction vs. Logistic Regression: A Learning-Curve Analysis. |
Journal of Machine Learning Research |
2003 |
DBLP BibTeX RDF |
|
| 1 | Foster J. Provost, Pedro Domingos |
Tree Induction for Probability-Based Ranking. |
Machine Learning |
2003 |
DBLP DOI BibTeX RDF |
Laplace correction, classification, decision trees, ranking, bagging, cost-sensitive learning, probability estimation |
| 1 | Claudia Perlich, Foster J. Provost, Sofus A. Macskassy |
Predicting citation rates for physics papers: constructing features for an ordered probit model. |
SIGKDD Explorations |
2003 |
DBLP DOI BibTeX RDF |
|
| 1 | Shawndra Hill, Foster J. Provost |
The myth of the double-blind review?: author identification using only citations. |
SIGKDD Explorations |
2003 |
DBLP DOI BibTeX RDF |
KDD Cup competition, author identification, discriminative self-citations, social network analysis, vector-space model, relational learning |
| 1 | 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 |
DBLP DOI BibTeX RDF |
|
| 1 | Claudia Perlich, Foster J. Provost |
Aggregation-based feature invention and relational concept classes. |
KDD |
2003 |
DBLP DOI BibTeX RDF |
aggregation, relational learning, feature construction, constructive induction, propositionalization |
| 1 | Foster J. Provost, Tom Fawcett |
Robust Classification for Imprecise Environments. |
Machine Learning |
2001 |
DBLP DOI BibTeX RDF |
|
| 1 | Ron Kohavi, Foster J. Provost |
Applications of Data Mining to Electronic Commerce. |
Data Min. Knowl. Discov. |
2001 |
DBLP DOI BibTeX RDF |
|
| 1 | Maytal Saar-Tsechansky, Foster J. Provost |
Active Learning for Class Probability Estimation and Ranking. |
IJCAI |
2001 |
DBLP BibTeX RDF |
|
| 1 | Sofus A. Macskassy, Haym Hirsh, Foster J. Provost, Ramesh Sankaranarayanan, Vasant Dhar |
Intelligent Information Triage. |
SIGIR |
2001 |
DBLP BibTeX RDF |
|
| 1 | 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 |
DBLP DOI BibTeX RDF |
|
| 1 | Ron Kohavi, Foster J. Provost |
Applications of Data Mining to Electronic Commerce |
CoRR |
2000 |
DBLP BibTeX RDF |
|
| 1 | Foster J. Provost, Tom Fawcett |
Robust Classification for Imprecise Environments |
CoRR |
2000 |
DBLP BibTeX RDF |
|
| 1 | Foster J. Provost, Andrea Pohoreckyj Danyluk |
Problem Definition, Data Cleaning, and Evaluation: A Classifier Learning Case Study. |
Informatica (Slovenia) |
1999 |
DBLP BibTeX RDF |
|
| 1 | Foster J. Provost, Venkateswarlu Kolluri |
A Survey of Methods for Scaling Up Inductive Algorithms. |
Data Min. Knowl. Discov. |
1999 |
DBLP DOI BibTeX RDF |
|
| 1 | Foster J. Provost, David Jensen, Tim Oates |
Efficient Progressive Sampling. |
KDD |
1999 |
DBLP DOI BibTeX RDF |
|
| 1 | Tom Fawcett, Foster J. Provost |
Activity Monitoring: Noticing Interesting Changes in Behavior. |
KDD |
1999 |
DBLP DOI BibTeX RDF |
|
| 1 | Foster J. Provost, Ron Kohavi |
Guest Editors' Introduction: On Applied Research in Machine Learning. |
Machine Learning |
1998 |
DBLP DOI BibTeX RDF |
|
| 1 | Tom Fawcett, Ira J. Haimowitz, Foster J. Provost, Salvatore J. Stolfo |
AI Approaches to Fraud Detection and Risk Management. |
AI Magazine |
1998 |
DBLP BibTeX RDF |
|
| 1 | Foster J. Provost, Tom Fawcett, Ron Kohavi |
The Case against Accuracy Estimation for Comparing Induction Algorithms. |
ICML |
1998 |
DBLP BibTeX RDF |
|
| 1 | Foster J. Provost, Tom Fawcett |
Robust Classification Systems for Imprecise Environments. |
AAAI/IAAI |
1998 |
DBLP BibTeX RDF |
|
| 1 | Tom Fawcett, Foster J. Provost |
Adaptive Fraud Detection. |
Data Min. Knowl. Discov. |
1997 |
DBLP DOI BibTeX RDF |
|
| 1 | Foster J. Provost, Venkateswarlu Kolluri |
Scaling Up Inductive Algorithms: An Overview. |
KDD |
1997 |
DBLP BibTeX RDF |
|
| 1 | John M. Aronis, Foster J. Provost |
Increasing the Efficiency of Data Mining Algorithms with Breadth-First Marker Propagation. |
KDD |
1997 |
DBLP BibTeX RDF |
|
| 1 | Foster J. Provost, Tom Fawcett |
Analysis and Visualization of Classifier Performance: Comparison under Imprecise Class and Cost Distributions. |
KDD |
1997 |
DBLP BibTeX RDF |
|
| 1 | Foster J. Provost, John M. Aronis |
Scaling Up Inductive Learning with Massive Parallelism. |
Machine Learning |
1996 |
DBLP DOI BibTeX RDF |
|
| 1 | Foster J. Provost, Daniel N. Hennessy |
Scaling Up: Distributed Machine Learning with Cooperation. |
AAAI/IAAI, Vol. 1 |
1996 |
DBLP BibTeX RDF |
|
| 1 | Tom Fawcett, Foster J. Provost |
Combining Data Mining and Machine Learning for Effective User Profiling. |
KDD |
1996 |
DBLP BibTeX RDF |
|
| 1 | John M. Aronis, Foster J. Provost, Bruce G. Buchanan |
Exploiting Background Knowledge in Automated Discovery. |
KDD |
1996 |
DBLP BibTeX RDF |
|
| 1 | Foster J. Provost, Bruce G. Buchanan |
Inductive Policy: The Pragmatics of Bias Selection. |
Machine Learning |
1995 |
DBLP DOI BibTeX RDF |
|
| 1 | Foster J. Provost, Daniel N. Hennessy |
Distributed Machine Learning: Scaling Up with Coarse-grained Parallelism. |
ISMB |
1994 |
DBLP BibTeX RDF |
|
| 1 | John M. Aronis, Foster J. Provost |
Efficiently Constructing Relational Features from Background Knowledge for Inductive Machine Learning. |
KDD Workshop |
1994 |
DBLP BibTeX RDF |
|
| 1 | Andrea Pohoreckyj Danyluk, Foster J. Provost |
Small Disjuncts in Action: Learning to Diagnose Errors in the Local Loop of the Telephone Network. |
ICML |
1993 |
DBLP BibTeX RDF |
|
| 1 | Foster J. Provost |
Iterative Weakening: Optimal and Near-Optimal Policies for the Selection of Search Bias. |
AAAI |
1993 |
DBLP BibTeX RDF |
|
| 1 | 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 |
DBLP DOI BibTeX RDF |
|
| 1 | Foster J. Provost, Bruce G. Buchanan |
Inductive Strengthening: the Effects of a Simple Heuristic for Restricting Hypothesis Space Search. |
AII |
1992 |
DBLP DOI BibTeX RDF |
|
| 1 | Foster J. Provost |
ClimBS: Searching the Bias Space. |
ICTAI |
1992 |
DBLP BibTeX RDF |
|
| 1 | Foster J. Provost, Bruce G. Buchanan |
Inductive Policy. |
AAAI |
1992 |
DBLP BibTeX RDF |
|
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