- Online Active Inference and Learning Josh Attenberg
- The Relational Vector-space Model and Industry Classification Abraham Bernstein
- Tree Induction vs. Logistic Regression: A Learning{Curve Analysis
- Efficiently Constructing Relational Features from Background Knowledge for Inductive Machine Learning
- H1.9.1 Telecommunications Network Diagnosis Andrea Pohoreckyj Danyluk
- , , 1--42 () fl Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
- Mach Learn (2006) 62: 65105 DOI 10.1007/s10994-006-6064-1
- Social network collaborative filtering RONG ZHENG, DENNIS WILKINSON & FOSTER PROVOST1
- Exploiting Background Knowledge in Automated Discovery John M. Aronis
- Modeling Complex NetworksModeling Complex Networks For (Electronic) CommerceFor (Electronic) Commerce
- Efficient Progressive Sampling Foster Provost
- Scaling Up: Distributed Machine Learning with Cooperation * Foster John Provost
- This is a draft of a paper that is to appear in the IEEE Transactions on Knowledge and Data Engineering
- Why Label when you can Search? Alternatives to Active Learning for Applying Human Resources to Build
- Increasing the Efficiency of Data Mining Algorithms with BreadthFirst Marker Propagation
- New York University -Stern School of Business Working paper CeDER-11-01
- Inactive Learning? Difficulties Employing Active Learning in Practice
- Active Inference and Learning for Classifying Streams Josh Attenberg josh@cis.poly.edu
- Guided Feature Labeling for Budget-Sensitive Learning Under Extreme Class Imbalance
- Active Feature-Value Acquisition Maytal Saar-Tsechansky
- Journal of Machine Learning Research 1 (2007) 1-48 Submitted 4/00; Published 10/00 Handling Missing Values when Applying Classi...cation
- Machine Learning, 54, 153178, 2004 c 2004 Kluwer Academic Publishers. Manufactured in The Netherlands.
- CeDER Working Paper #IS-01-03, Stern School of Business, New York University, NY, NY 10012 November 7, 2001
- Machine Learning from Imbalanced Data Sets 101 Extended Abstract
- Well-Trained PETs: Improving Probability Estimation Trees Foster Provost, New York University
- Active Learning for Class Probability Estimation and Ranking Maytal Saar-Tsechansky and Foster Provost
- 1 2003 Foster Provost The Role of Applications
- Audience Selection for On-line Brand Advertising: Privacy-friendly Social Network Targeting
- Robust Classi cation for Imprecise Environments Foster Provost (provost@acm.org)
- Rule-space Search for Knowledge-based Discovery Authors: Foster Provost
- Scaling Up Inductive Algorithms: An Overview Foster Provost Venkateswarlu Kolluri
- Machine Learning, vv, 1--6 (1998) fl 1998 Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
- Provost2009,2010 MachineLearningforDisplayAdvertising
- To appear in Proc. Sixth Workshop on eBusiness (WeB2007) Social Network Collaborative Filtering: Preliminary Results
- Quality Management on Amazon Mechanical Turk Panagiotis G. Ipeirotis
- , , 1--15 () fl Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
- Statistical Science 2006, Vol. 21, No. 2, 256276
- Get Another Label? Improving Data Quality and Data Mining Using Multiple, Noisy Labelers
- Online Active Inference and Learning Josh Attenberg
- Selective Data Acquisition for Machine Josh Attenberg
- Beat the Machine: Challenging Workers to Find the Unknown Josh Attenberg
