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1
Electrical entropy
2
Curse of dimensionality
3
Neural network functions
4
Hierarchical basis
5
Approximation properties
6
Conclusion
7
Isotropic spaces
8
Deep networks
9
Gradient neuron method
10
Frequency principle
11
Relu
12
Accuracy
13
Rate of convergence
14
Multigrade method
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore a comprehensive lecture on the finite neuron method in this 1 hour 25 minute conference talk by Jinchao Xu at the Centre International de Rencontres Mathématiques in Marseille, France. Delve into topics such as electrical entropy, the curse of dimensionality, neural network functions, and hierarchical basis. Examine approximation properties, isotropic spaces, deep networks, and the gradient neuron method. Investigate the frequency principle, ReLU activation, accuracy, rate of convergence, and the multigrade method. Access this video and other mathematical talks on CIRM's Audiovisual Mathematics Library, featuring chapter markers, keywords, abstracts, bibliographies, and multi-criteria search functionality for an enhanced learning experience.

Finite Neuron Method - Lecture 2

Centre International de Rencontres Mathématiques
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