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» Dynamic power management using machine learning
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ICALT
2007
IEEE
15 years 6 months ago
Integrating Dynamic Program Visualization into BlueJ: the Jeliot 3 Extension
Previous research on program visualization tools has suggested that both static and dynamic aspects of the program shall be shown to novice students. We attempted to expand the st...
Niko Myller, Roman Bednarik, Andrés Moreno
ICML
2010
IEEE
15 years 27 days ago
Power Iteration Clustering
We present a simple and scalable graph clustering method called power iteration clustering (PIC). PIC finds a very low-dimensional embedding of a dataset using truncated power ite...
Frank Lin, William W. Cohen
ML
2008
ACM
14 years 11 months ago
Layered critical values: a powerful direct-adjustment approach to discovering significant patterns
Standard pattern discovery techniques, such as association rules, suffer an extreme risk of finding very large numbers of spurious patterns for many knowledge discovery tasks. The...
Geoffrey I. Webb
IPSN
2003
Springer
15 years 5 months ago
Sentry-Based Power Management in Wireless Sensor Networks
This paper presents a sentry-based approach to power management in wireless sensor networks for applications such as intruder detection and tracking. To minimize average power cons...
Jonathan Hui, Zhiyuan Ren, Bruce H. Krogh
SIES
2007
IEEE
15 years 6 months ago
Process Oriented Power Management
— Though modern operating systems have a capable of controlling the power consumption using the DVFS (Dynamic Voltage and Frequency Scaling) mechanism, it is controlled for some ...
Daisuke Miyakawa, Yutaka Ishikawa