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KDD
2009
ACM
180views Data Mining» more  KDD 2009»
14 years 9 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
CVPR
2010
IEEE
14 years 5 months ago
Far-Sighted Active Learning on a Budget for Image and Video Recognition
Active learning methods aim to select the most informative unlabeled instances to label first, and can help to focus image or video annotations on the examples that will most impr...
Sudheendra Vijayanarasimhan, Prateek Jain, Kristen...
HICSS
2000
IEEE
134views Biometrics» more  HICSS 2000»
14 years 1 months ago
Peer-to-Peer Valuation as a Mechanism for Reinforcing Active Learning in Virtual Communities: Actualizing Social Exchange Theory
As knowledge becomes the primary focus of work in many industries, virtual communities and groups are emerging as part of new organizational forms. Within these virtual forms, eff...
Amrit Tiwana, Ashley A. Bush
SDM
2004
SIAM
187views Data Mining» more  SDM 2004»
13 years 10 months ago
Class-Specific Ensembles for Active Learning
In many real-world tasks of image classification, limited amounts of labeled data are available to train automatic classifiers. Consequently, extensive human expert involvement is...
Amit Mandvikar, Huan Liu
EWCBR
2000
Springer
14 years 15 days ago
Active Delivery for Lessons Learned Systems
Lessons learned processes, and software systems that support them, have been developed by many organizations (e.g., all USA military branches, NASA, several Department of Energy or...
Rosina Weber, David W. Aha, Héctor Mu&ntild...