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153
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KDD
2009
ACM
180views Data Mining» more  KDD 2009»
16 years 4 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
TCIAIG
2010
14 years 10 months ago
Game Bot Detection via Avatar Trajectory Analysis
The objective of this work is to automatically detect the use of game bots in online games based on the trajectories of account users. Online gaming has become one of the most popu...
Hsing-Kuo Pao, Kuan-Ta Chen, Hong-Chung Chang
113
Voted
CVPR
2010
IEEE
15 years 12 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...
142
Voted
HICSS
2000
IEEE
134views Biometrics» more  HICSS 2000»
15 years 8 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
EWCBR
2000
Springer
15 years 7 months 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...