Subject
3 entries
Svm
Bookmarks
The Kernel Trick
Eric Kim's explanation of the kernel trick in support vector machines — how kernels enable SVMs to classify non-linearly separable data by implicitly mapping it to a higher-dimensional space. One of the cleaner intuitive explanations of a mathematically dense concept.
Deep Support Vector Machines
A video lecture on Deep Support Vector Machines from ROKS 2013 — hybrid architectures combining deep feature learning with SVM classification. A snapshot of the moment researchers explored whether SVMs and deep learning could coexist before end-to-end networks won out.
Introduction to One-Class Support Vector Machines
A practical introduction to one-class SVMs — the variant of Support Vector Machines used for anomaly detection and novelty detection when you only have examples of normal behavior. Useful when collecting labeled anomaly examples is impractical or impossible.