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» Dynamic power management using machine learning
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112
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ICML
2006
IEEE
16 years 4 months ago
Predictive linear-Gaussian models of controlled stochastic dynamical systems
We introduce the controlled predictive linearGaussian model (cPLG), a model that uses predictive state to model discrete-time dynamical systems with real-valued observations and v...
Matthew R. Rudary, Satinder P. Singh
CODES
2001
IEEE
15 years 7 months ago
Hybrid global/local search strategies for dynamic voltage scaling in embedded multiprocessors
In this paper, we explore a hybrid global/local search optimization framework for dynamic voltage scaling in embedded multiprocessor systems. The problem is to find, for a multipr...
Neal K. Bambha, Shuvra S. Bhattacharyya, Jürg...
138
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ICRA
2007
IEEE
189views Robotics» more  ICRA 2007»
15 years 9 months ago
Context Estimation and Learning Control through Latent Variable Extraction: From discrete to continuous contexts
— Recent advances in machine learning and adaptive motor control have enabled efficient techniques for online learning of stationary plant dynamics and it’s use for robust pre...
Georgios Petkos, Sethu Vijayakumar
IWOMP
2009
Springer
15 years 8 months ago
Dynamic Task and Data Placement over NUMA Architectures: An OpenMP Runtime Perspective
Abstract. Exploiting the full computational power of current hierarchical multiprocessor machines requires a very careful distribution of threads and data among the underlying non-...
François Broquedis, Nathalie Furmento, Bric...
ADC
2010
Springer
214views Database» more  ADC 2010»
14 years 10 months ago
Building a dynamic classifier for large text data collections
Due to the lack of in-built tools to navigate the web, people have to use external solutions to find information. The most popular of these are search engines and web directories....
Pavel Kalinov, Bela Stantic, Abdul Sattar