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» Experimental perspectives on learning from imbalanced data
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COLING
2010
14 years 4 months ago
A Comparison of Models for Cost-Sensitive Active Learning
Active Learning (AL) is a selective sampling strategy which has been shown to be particularly cost-efficient by drastically reducing the amount of training data to be manually ann...
Katrin Tomanek, Udo Hahn
CHI
2004
ACM
15 years 10 months ago
Lessons learned using ubiquitous sensors for data collection in real homes
Interface design for the home requires a realistic understanding of the complexity and richness of the human activities that go on there; it is our goal to develop tools that enab...
Jennifer Beaudin, Stephen S. Intille, Emmanuel Mun...
ICML
2009
IEEE
15 years 10 months ago
Learning instance specific distances using metric propagation
In many real-world applications, such as image retrieval, it would be natural to measure the distances from one instance to others using instance specific distance which captures ...
De-Chuan Zhan, Ming Li, Yu-Feng Li, Zhi-Hua Zhou
CHI
2003
ACM
15 years 10 months ago
MiTAP for real users, real data, real problems
The MiTAP system was developed as an experimental prototype using human language technologies for monitoring disease outbreaks. The system provides timely, multi-lingual, global i...
Laurie E. Damianos, Steve Wohlever, Robyn Kozierok...
AAAI
2004
14 years 11 months ago
Towards Autonomic Computing: Adaptive Job Routing and Scheduling
Computer systems are rapidly becoming so complex that maintaining them with human support staffs will be prohibitively expensive and inefficient. In response, visionaries have beg...
Shimon Whiteson, Peter Stone