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DAC
2004
ACM
16 years 7 months ago
System design for DSP applications in transaction level modeling paradigm
In this paper, we systematically define three transaction level TLMs), which reside at different levels of abstraction between the functional and the implementation model of a DSP...
Abhijit K. Deb, Axel Jantsch, Johnny Öberg
ICML
2009
IEEE
16 years 7 months ago
Constraint relaxation in approximate linear programs
Approximate Linear Programming (ALP) is a reinforcement learning technique with nice theoretical properties, but it often performs poorly in practice. We identify some reasons for...
Marek Petrik, Shlomo Zilberstein
ICML
2008
IEEE
16 years 7 months ago
Fast estimation of first-order clause coverage through randomization and maximum likelihood
In inductive logic programming, subsumption is a widely used coverage test. Unfortunately, testing -subsumption is NP-complete, which represents a crucial efficiency bottleneck fo...
Filip Zelezný, Ondrej Kuzelka
ICML
2000
IEEE
16 years 7 months ago
Learning Probabilistic Models for Decision-Theoretic Navigation of Mobile Robots
Decision-theoretic reasoning and planning algorithms are increasingly being used for mobile robot navigation, due to the signi cant uncertainty accompanying the robots' perce...
Daniel Nikovski, Illah R. Nourbakhsh
ICML
1995
IEEE
16 years 7 months ago
Stable Function Approximation in Dynamic Programming
The success ofreinforcement learninginpractical problems depends on the ability to combine function approximation with temporal di erence methods such as value iteration. Experime...
Geoffrey J. Gordon