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BMVC
2000
15 years 4 months ago
Estimating Vision Parameters given Data with Covariances
A new parameter estimation method is presented, applicable to many computer vision problems. It operates under the assumption that the data (typically image point locations) are a...
Wojciech Chojnacki, Michael J. Brooks, Anton van d...
130
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DAC
2005
ACM
16 years 4 months ago
Incremental exploration of the combined physical and behavioral design space
Achieving design closure is one of the biggest headaches for modern VLSI designers. This problem is exacerbated by high-level design automation tools that ignore increasingly impo...
Zhenyu (Peter) Gu, Jia Wang, Robert P. Dick, Hai Z...
123
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TVLSI
2010
14 years 10 months ago
LOPASS: A Low-Power Architectural Synthesis System for FPGAs With Interconnect Estimation and Optimization
In this paper, we present a low-power architectural synthesis system (LOPASS) for field-programmable gate-array (FPGA) designs with interconnect power estimation and optimization. ...
Deming Chen, Jason Cong, Yiping Fan, Lu Wan
162
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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
116
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AAAI
2008
15 years 5 months ago
Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
Hirotaka Hachiya, Takayuki Akiyama, Masashi Sugiya...