@inproceedings{36cd6d7e4e1646efb55b4fa7a271aea8,
title = "How hard is inference for structured prediction?",
abstract = "Structured prediction tasks in machine learning involve the simultaneous prediction of multiple labels. This is often done by maximizing a score function on the space of labels, which decomposes as a sum of pairwise elements, each depending on two specific labels. The goal of this paper is to develop a theoretical explanation of the empirical effectiveness of heuristic inference algorithms for solving such structured prediction problems. We study the minimum-achievable expected Hamming error in such problems, highlighting the case of 2D grid graphs, which are common in machine vision applications. Our main theorems provide tight upper and lower bounds on this error, as well as a polynomial-time algorithm that achieves the bound.",
author = "Amir Globerson and Tim Roughgarden and David Sontag and Cafer Yildirim",
note = "Publisher Copyright: {\textcopyright} Copyright 2015 by International Machine Learning Society (IMLS). All rights reserved.; 32nd International Conference on Machine Learning, ICML 2015 ; Conference date: 06-07-2015 Through 11-07-2015",
year = "2015",
language = "الإنجليزيّة",
series = "32nd International Conference on Machine Learning, ICML 2015",
pages = "2171--2180",
editor = "Francis Bach and David Blei",
booktitle = "32nd International Conference on Machine Learning, ICML 2015",
}