Pages that link to "Item:Q5243078"
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The following pages link to Neural Approximations for Optimal Control and Decision (Q5243078):
Displaying 18 items.
- Neural computation for robust approximate pole assignment (Q1305913) (← links)
- Optimal neurocontroller synthesis for impulse-driven systems (Q1784539) (← links)
- Computational design of innovative mechanical metafilters via adaptive surrogate-based optimization (Q2022061) (← links)
- An intrinsic material tailoring approach for functionally graded axisymmetric hollow bodies under plane elasticity (Q2028518) (← links)
- Encoded value-at-risk: a machine learning approach for portfolio risk measurement (Q2168136) (← links)
- A mean-field optimal control formulation of deep learning (Q2319864) (← links)
- Poisoning finite-horizon Markov decision processes at design time (Q2668608) (← links)
- Quantitative estimates for neural network operators implied by the asymptotic behaviour of the sigmoidal activation functions (Q2675943) (← links)
- (Q4257216) (← links)
- Long-Run Risk-Sensitive Impulse Control (Q5130920) (← links)
- Reinforced ART (ReART) for Online Neural Control (Q5302446) (← links)
- SIMPLE NEURAL NETWORKS THAT OPTIMIZE DECISIONS (Q5318370) (← links)
- Approximation error for neural network operators by an averaged modulus of smoothness (Q6093307) (← links)
- Optimized ensemble value function approximation for dynamic programming (Q6112619) (← links)
- Event-triggered integral reinforcement learning for nonzero-sum games with asymmetric input saturation (Q6488708) (← links)
- Best approximation and inverse results for neural network operators (Q6595826) (← links)
- Voronoi recursive binary trees for the optimization of nonlinear functionals (Q6619764) (← links)
- Asymptotic analysis of neural network operators employing the Hardy-Littlewood maximal inequality (Q6649179) (← links)