Oct 26, 2017 · This approach has the advantage that rigorous error estimates and convergence results can be established.
In a series of papers, we introduce an alternative approach by exploring the optimal con- trol viewpoint of deep learning (E, 2017). Our focus will be on ideas ...
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Maximum Principle Based Algorithms for Deep Learning. Qianxiao Li, Long Chen, Cheng Tai, Weinan E. Journal of Machine Learning Research 18 165:1–165:29.
Jan 1, 2017 · The continuous dynamical system approach to deep learning is explored in order to devise alternative frameworks for training algorithms.
This is an iterative algorithm that alternates between solving the Hamiltonian system for the states and costates and finding the optimal parameters at each ...
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The continuous dynamical system approach to deep learning is explored in order to devise alternative frameworks for training algorithms using the ...
We discuss the dynamical systems approach to deep learning, in which training is recast as a control problem and this allows us to formulate necessary ...
Jan 12, 2018 · In this talk, we present an alternative viewpoint on the training of deep neural networks. Instead of an optimization problem, we may view ...
Pontryagin Maximum Principle (PMP) leads to algorithm proposed in Zhang et al. ... Maximum principle based algorithms for deep learning. The Journal of Machine ...
The goal of this section is to discuss algorithms for solving (2) based on the maximum principle. ... Maximum principle based algorithms for deep learning.