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JAT
2006
64views more  JAT 2006»
14 years 9 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 3 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 9 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 9 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
14 years 11 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