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» Dynamic power management using machine learning
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114
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ECML
2007
Springer
15 years 9 months ago
Learning an Outlier-Robust Kalman Filter
We introduce a modified Kalman filter that performs robust, real-time outlier detection, without the need for manual parameter tuning by the user. Systems that rely on high quali...
Jo-Anne Ting, Evangelos Theodorou, Stefan Schaal
104
Voted
ECML
2006
Springer
15 years 7 months ago
Learning Process Models with Missing Data
Abstract. In this paper, we review the task of inductive process modeling, which uses domain knowledge to compose explanatory models of continuous dynamic systems. Next we discuss ...
Will Bridewell, Pat Langley, Steve Racunas, Stuart...
EGC
2005
Springer
15 years 9 months ago
M-Grid: Using Ubiquitous Web Technologies to Create a Computational Grid
Abstract. There are many potential users and uses for grid computing. However, the concept of sharing computing resources excites security concerns and, whilst being powerful and f...
Robert John Walters, Stephen Crouch
ICCD
2003
IEEE
167views Hardware» more  ICCD 2003»
16 years 13 days ago
Virtual Page Tag Reduction for Low-power TLBs
We present a methodology for a power-optimized, software-controlled Translation Lookaside Buffer (TLB) organization. A highly reduced number of Virtual Page Number (VPN) bits suf...
Peter Petrov, Alex Orailoglu
181
Voted
CISIS
2011
IEEE
14 years 3 months ago
Improving Scheduling Techniques in Heterogeneous Systems with Dynamic, On-Line Optimisations
—Computational performance increasingly depends on parallelism, and many systems rely on heterogeneous resources such as GPUs and FPGAs to accelerate computationally intensive ap...
Marcin Bogdanski, Peter R. Lewis, Tobias Becker, X...