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kernel-methods

Data challenge for the course "machine learning with kernel methods"

This code reimplements the following papers in Python and Cython:

Mairal, Julien and Koniusz, Piotr and Harchaoui, Zaid and Schmid, Cordelia. Convolutional kernel networks. NIPS 2014.

Mairal, Julien. End-to-end kernel learning with supervised convolutional kernel networks. NIPS 2016.

Hsieh, Cho-Jui and Chang, Kai-Wei and Lin, Chih-Jen and Keerthi, S Sathiya and Sundararajan, Sellamanickam. A dual coordinate descent method for large-scale linear SVM. Proceedings of the 25th international conference on Machine learning. ACM, 2008.

Installation

pip install -r requirements.txt
make

Utilisation for Data Challenge

python start.py

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Data challenge for the course "machine learning with kernel methods"

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