Feb 3, 2023 · Simulation results demonstrate that the proposed algorithm outperforms the conventional method in terms of improved accuracy in output with a ...
We consider recent work of [ 18 ] and [ 9 ], where deep learning neural networks have been interpreted as discretisations of an optimal control problem ...
... an optimal control problem subject to an ordinary ... An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural Networks.
[PDF] Dynamic System and Optimal Control Perspective of Deep Learning
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▫Optimal control perspective for deep network training ... An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural Networks.
Jan 25, 2023 · We represent the optimal control functions by neural networks and solve optimal control problems by deep learning techniques.
Jul 28, 2020 · • Qianxiao Li Shuji Hao, An Optimal Control Approach to Deep Learning and. Applications to Discrete-Weight Neural Networks. • Qianxiao Li ...
The paper observes a similarity between the stochastic optimal control of discrete dynamical systems and the learning multilayer neural networks. It focuses on ...
to apply the E-MSA to train neural networks that have discrete weights (e.g. those that ... Optimal Control Applications and Methods, 3(2):. 101–114, 1982.
However, we check correctness of it only on finite number of observed data. We develop an optimal control approach allowing to find approximation of an unknown ...
An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural Networks: arXiv19. Optimizing Millions of Hyperparameters by Implicit ...