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ALIFE
2002
13 years 7 months ago
Ant Colony Optimization and Stochastic Gradient Descent
In this paper, we study the relationship between the two techniques known as ant colony optimization (aco) and stochastic gradient descent. More precisely, we show that some empir...
Nicolas Meuleau, Marco Dorigo
CDC
2010
IEEE
117views Control Systems» more  CDC 2010»
13 years 2 months ago
A symmetric structure of variational and adjoint systems of stochastic Hamiltonian systems
Abstract-- The authors have extended deterministic portHamiltonian systems into stochastic dynamical systems which are described by stochastic differential equations written in the...
Satoshi Satoh, Kenji Fujimoto
ALT
2007
Springer
14 years 4 months ago
Learning Rational Stochastic Tree Languages
Abstract. We consider the problem of learning stochastic tree languages, i.e. probability distributions over a set of trees T(F), from a sample of trees independently drawn accordi...
François Denis, Amaury Habrard
SIAMCO
2000
117views more  SIAMCO 2000»
13 years 7 months ago
The O.D.E. Method for Convergence of Stochastic Approximation and Reinforcement Learning
It is shown here that stability of the stochastic approximation algorithm is implied by the asymptotic stability of the origin for an associated ODE. This in turn implies convergen...
Vivek S. Borkar, Sean P. Meyn
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
14 years 1 months ago
Learning noise
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Michael D. Schmidt, Hod Lipson