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» Dynamic power management using machine learning
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ICML
2009
IEEE
16 years 4 months ago
Boosting with structural sparsity
Despite popular belief, boosting algorithms and related coordinate descent methods are prone to overfitting. We derive modifications to AdaBoost and related gradient-based coordin...
John Duchi, Yoram Singer
129
Voted
SUTC
2006
IEEE
15 years 9 months ago
Energy and Communication Efficient Group Key Management Protocol for Hierarchical Sensor Networks
- In this paper, we describe a group key management protocol for hierarchical sensor networks where instead of using pre-deployed keys, each sensor node generates a partial key dyn...
Biswajit Panja, Sanjay Kumar Madria, Bharat K. Bha...
148
Voted
AAAI
2008
15 years 5 months ago
Learning to Improve Earth Observation Flight Planning
This paper describes a method and system for integrating machine learning with planning and data visualization for the management of mobile sensors for Earth science investigation...
Robert A. Morris, Nikunj C. Oza, Leslie Keely, Eli...
PLDI
2009
ACM
15 years 10 months ago
Dynamic software updates: a VM-centric approach
Software evolves to fix bugs and add features. Stopping and restarting programs to apply changes is inconvenient and often costly. Dynamic software updating (DSU) addresses this ...
Suriya Subramanian, Michael W. Hicks, Kathryn S. M...
139
Voted
ECCV
2002
Springer
16 years 5 months ago
Learning to Parse Pictures of People
The detection of people is one of the foremost problems for indexing, browsing and retrieval of video. The main difficulty is the large appearance variations caused by action, clot...
Rémi Ronfard, Cordelia Schmid, Bill Triggs