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CORR
2010
Springer
204views Education» more  CORR 2010»
13 years 6 months ago
Predictive State Temporal Difference Learning
We propose a new approach to value function approximation which combines linear temporal difference reinforcement learning with subspace identification. In practical applications...
Byron Boots, Geoffrey J. Gordon
FPL
2007
Springer
124views Hardware» more  FPL 2007»
14 years 1 months ago
A Quantitative Prediction Model for Hardware/Software Partitioning
An important step in Heterogeneous System Development is Hardware/Software Partitioning. This process involves exploring a huge design space. By using profiling to select hot-spo...
Roel Meeuws, Yana Yankova, Koen Bertels, Georgi Ga...
ICCAD
2004
IEEE
145views Hardware» more  ICCAD 2004»
14 years 4 months ago
Asymptotic probability extraction for non-normal distributions of circuit performance
While process variations are becoming more significant with each new IC technology generation, they are often modeled via linear regression models so that the resulting performanc...
Xin Li, Jiayong Le, Padmini Gopalakrishnan, Lawren...
ESWA
2006
86views more  ESWA 2006»
13 years 7 months ago
Modeling consumer acceptance probabilities
This paper investigates how to estimate the likelihood of a customer accepting a loan offer as a function of the offer parameters and how to choose the optimal set of parameters f...
L. C. Thomas, Ki Mun Jung, Steve D. Thomas, Y. Wu
CDC
2010
IEEE
150views Control Systems» more  CDC 2010»
13 years 2 months ago
Nonlinear hybrid system identification with kernel models
Abstract-- This paper focuses on the identification of nonlinear hybrid systems involving unknown nonlinear dynamics. The proposed method extends the framework of [1] by introducin...
Fabien Lauer, Gérard Bloch, René Vid...