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ESANN
2004
15 years 3 months ago
High-accuracy value-function approximation with neural networks applied to the acrobot
Several reinforcement-learning techniques have already been applied to the Acrobot control problem, using linear function approximators to estimate the value function. In this pape...
Rémi Coulom
GECCO
2008
Springer
124views Optimization» more  GECCO 2008»
15 years 3 months ago
Introducing MONEDA: scalable multiobjective optimization with a neural estimation of distribution algorithm
In this paper we explore the model–building issue of multiobjective optimization estimation of distribution algorithms. We argue that model–building has some characteristics t...
Luis Martí, Jesús García, Ant...
ISCAS
1994
IEEE
104views Hardware» more  ISCAS 1994»
15 years 6 months ago
Stereo Correspondence with Discrete-Time Cellular Neural Networks
In this paper, we propose a new approach of solving the stereopsis problem with a discrete-time cellular neural network(DTCNN) where each node has connectionsonly with its local n...
Sungjun Park, Seung-Jai Min, Soo-Ik Chae
ISNN
2007
Springer
15 years 8 months ago
Neural-Based Separating Method for Nonlinear Mixtures
A neural-based method for source separation in nonlinear mixture is proposed in this paper. A cost function, which consists of the mutual information and partial moments of the out...
Ying Tan
IWANN
2009
Springer
15 years 9 months ago
Optimising Machine-Learning-Based Fault Prediction in Foundry Production
Abstract. Microshrinkages are known as probably the most difficult defects to avoid in high-precision foundry. The presence of this failure renders the casting invalid, with the su...
Igor Santos, Javier Nieves, Yoseba K. Penya, Pablo...