Fast and Scalable Structural SVM with Slack Rescaling
Abstract
We present an efficient method for training slack-rescaled structural SVM. Although finding the most violating label in a margin-rescaled formulation is often easy since the target function decomposes with respect to the structure, this is not the case for a slack-rescaled formulation, and finding the most violated label might be very difficult. Our core contribution is an efficient method for finding the most-violating-label in a slack-rescaled formulation, given an oracle that returns the most-violating-label in a (slightly modified) margin-rescaled formulation. We show that our method enables accurate and scalable training for slack-rescaled SVMs, reducing runtime by an order of magnitude compared to previous approaches to slack-rescaled SVMs.
Cite
@article{arxiv.1510.06002,
title = {Fast and Scalable Structural SVM with Slack Rescaling},
author = {Heejin Choi and Ofer Meshi and Nathan Srebro},
journal= {arXiv preprint arXiv:1510.06002},
year = {2015}
}