ml:support_vector_machines
Table of Contents
Support Vector Machines
Papers
- Optimizing SVMs in the primal:
- The idea for training neural networks with SVM loss came from Ronan Collobert's 2004 PhD Thesis and this paper: Collobert 2004 which has some conceptual errors (mainly that SVM loss is not Perceptron loss).
Structured SVM (SSVM)
Structured SVM with Latent Variables
- Learning Structural SVMs with Latent Variables Latent Structured SVM
ml/support_vector_machines.txt · Last modified: 2023/06/15 07:36 by 127.0.0.1