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» A Hybrid Learning Approach for TV Program Personalization
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90
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ICCV
2007
IEEE
15 years 11 months ago
An Invariant Large Margin Nearest Neighbour Classifier
The k-nearest neighbour (kNN) rule is a simple and effective method for multi-way classification that is much used in Computer Vision. However, its performance depends heavily on ...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
74
Voted
ICALT
2008
IEEE
15 years 4 months ago
A Framework for Semantic Group Formation
Collaboration has long been considered an effective approach to learning. However, forming optimal groups can be a time consuming and complex task. Different approaches have been ...
Asma Ounnas, Hugh C. Davis, David E. Millard
SIGSOFT
2008
ACM
15 years 10 months ago
Finding programming errors earlier by evaluating runtime monitors ahead-of-time
Runtime monitoring allows programmers to validate, for instance, the proper use of application interfaces. Given a property specification, a runtime monitor tracks appropriate run...
Eric Bodden, Patrick Lam, Laurie J. Hendren
88
Voted
KCAP
2009
ACM
15 years 4 months ago
Interactively shaping agents via human reinforcement: the TAMER framework
As computational learning agents move into domains that incur real costs (e.g., autonomous driving or financial investment), it will be necessary to learn good policies without n...
W. Bradley Knox, Peter Stone
KDD
2009
ACM
180views Data Mining» more  KDD 2009»
15 years 10 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