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JAT
2006
64views more  JAT 2006»
14 years 11 months ago
Nonlinear function approximation: Computing smooth solutions with an adaptive greedy algorithm
Opposed to linear schemes, nonlinear function approximation allows to obtain a dimension independent rate of convergence. Unfortunately, in the presence of data noise typical algo...
Andreas Hofinger
ATAL
2007
Springer
15 years 6 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
CORR
2010
Springer
170views Education» more  CORR 2010»
14 years 12 months ago
Global Optimization for Value Function Approximation
Existing value function approximation methods have been successfully used in many applications, but they often lack useful a priori error bounds. We propose a new approximate bili...
Marek Petrik, Shlomo Zilberstein
JAT
2008
57views more  JAT 2008»
14 years 11 months ago
Sharp approximations to the Bernoulli periodic functions by trigonometric polynomials
We obtain optimal trigonometric polynomials of a given degree N that majorize, minorize and approximate in L1(R/Z) the Bernoulli periodic functions. These are the periodic analogue...
Emanuel Carneiro
WSC
2004
15 years 1 months ago
Function-Approximation-Based Importance Sampling for Pricing American Options
Monte Carlo simulation techniques that use function approximations have been successfully applied to approximately price multi-dimensional American options. However, for many pric...
Nomesh Bolia, Sandeep Juneja, Paul Glasserman