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» Fast and Effective Task Scheduling in Heterogeneous Systems
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163
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ATAL
2005
Springer
15 years 9 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
126
Voted
DAC
2009
ACM
16 years 4 months ago
Process variation characterization of chip-level multiprocessors
Within-die variation in leakage power consumption is substantial and increasing for chip-level multiprocessors (CMPs) and multiprocessor systems-on-chip. Dealing with this problem...
Lide Zhang, Lan S. Bai, Robert P. Dick, Li Shang, ...
153
Voted
ICASSP
2011
IEEE
14 years 7 months ago
Belief theoretic methods for soft and hard data fusion
In many contexts, one is confronted with the problem of extracting information from large amounts of different types soft data (e.g., text) and hard data (from e.g., physics-based...
Thanuka Wickramarathne, Kamal Premaratne, Manohar ...
238
Voted
SENSYS
2006
ACM
15 years 9 months ago
Run-time dynamic linking for reprogramming wireless sensor networks
From experience with wireless sensor networks it has become apparent that dynamic reprogramming of the sensor nodes is a useful feature. The resource constraints in terms of energ...
Adam Dunkels, Niclas Finne, Joakim Eriksson, Thiem...
182
Voted
TPDS
2010
154views more  TPDS 2010»
14 years 10 months ago
Adaptive Workload Prediction of Grid Performance in Confidence Windows
Predicting grid performance is a complex task because heterogeneous resource nodes are involved in a distributed environment. Long execution workload on a grid is even harder to pr...
Yongwei Wu, Kai Hwang, Yulai Yuan, Weimin Zheng