4 ms·
I'm not aware of anything like a convolutional SVM, but I'm not terribly familiar with them. As I understand it SVMs are fundamentally shallow learners, and if
by Houshalter 9y ago
I'm not aware of anything like a convolutional SVM, but I'm not terribly familiar with them. As I understand it SVMs are fundamentally shallow learners, and if you try to hack them to make them deep and recurrent or convolutional, you just get weird NNs.
- xapata 9y agoShallow in the sense that SVMs are not layered, but the layering of a NN is only to enable the humble perceptron (logistic or sigmoid, usually) to model more complex functions. In contrast, the SVM doesn't need to layer, because the kernel can be arbitrarily complex.