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NIPS
2007
14 years 11 months ago
Random Sampling of States in Dynamic Programming
We combine three threads of research on approximate dynamic programming: sparse random sampling of states, value function and policy approximation using local models, and using lo...
Christopher G. Atkeson, Benjamin Stephens
POPL
2005
ACM
15 years 10 months ago
A probabilistic language based upon sampling functions
As probabilistic computations play an increasing role in solving various problems, researchers have designed probabilistic languages that treat probability distributions as primit...
Sungwoo Park, Frank Pfenning, Sebastian Thrun
TACAS
2001
Springer
160views Algorithms» more  TACAS 2001»
15 years 2 months ago
Hardware/Software Co-Design Using Functional Languages
In previous work we have developed and prototyped a silicon compiler which translates a functional language (SAFL) into hardware. Here we present a SAFL-level program transformati...
Alan Mycroft, Richard Sharp
JMLR
2012
13 years 11 days ago
Adaptive MCMC with Bayesian Optimization
This paper proposes a new randomized strategy for adaptive MCMC using Bayesian optimization. This approach applies to nondifferentiable objective functions and trades off explor...
Nimalan Mahendran, Ziyu Wang, Firas Hamze, Nando d...
IPPS
1998
IEEE
15 years 2 months ago
Automatic Differentiation for Message-Passing Parallel Programs
Many applications require the derivatives of functions defined by computer programs. Automatic differentiation (AD) is a means of developing code to compute the derivatives of com...
Paul D. Hovland, Christian H. Bischof