Support-vector networks, Corinna Cortes and Vladimir Vapnik, 1995Machine Learning, Vol. 20DOI: 10.1007/BF00994018 - The original paper introducing Support Vector Machines, outlining the maximal margin hyperplane and the core theoretical framework.
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Trevor Hastie, Robert Tibshirani, Jerome Friedman, 2009 (Springer) - A definitive textbook with a comprehensive chapter on Support Vector Machines, including detailed explanations of the maximal margin classifier and kernel methods.
1.4. Support Vector Machines, Scikit-learn developers, 2023 - The official user guide for Support Vector Machines in Scikit-learn, providing practical details on implementation and different kernel choices.
CS229 Lecture Notes: Support Vector Machines, Andrew Ng, 2018 - Comprehensive lecture notes from a renowned university course, offering clear derivations and explanations of SVM concepts, including the maximal margin classifier and kernels.