---
OA_place: repository
OA_type: gold
_id: '2051'
abstract:
- lang: eng
  text: We show that the usual score function for conditional Markov networks can
    be written as the expectation over the scores of their spanning trees. We also
    show that a small random sample of these output trees can attain a significant
    fraction of the margin obtained by the complete graph and we provide conditions
    under which we can perform tractable inference. The experimental results confirm
    that practical learning is scalable to realistic datasets using this approach.
article_processing_charge: No
author:
- first_name: Mario
  full_name: Marchand, Mario
  last_name: Marchand
- first_name: Su
  full_name: Hongyu, Su
  last_name: Hongyu
- first_name: Emilie
  full_name: Morvant, Emilie
  id: 4BAC2A72-F248-11E8-B48F-1D18A9856A87
  last_name: Morvant
  orcid: 0000-0002-8301-7240
- first_name: Juho
  full_name: Rousu, Juho
  last_name: Rousu
- first_name: John
  full_name: Shawe Taylor, John
  last_name: Shawe Taylor
citation:
  ama: 'Marchand M, Hongyu S, Morvant E, Rousu J, Shawe Taylor J. Multilabel structured
    output learning with random spanning trees of max-margin Markov networks. In:
    <i>Advances in Neural Information Processing Systems</i>. Vol 27. Neural Information
    Processing Systems Foundation; 2014.'
  apa: 'Marchand, M., Hongyu, S., Morvant, E., Rousu, J., &#38; Shawe Taylor, J. (2014).
    Multilabel structured output learning with random spanning trees of max-margin
    Markov networks. In <i>Advances in Neural Information Processing Systems</i> (Vol.
    27). Montreal, Canada: Neural Information Processing Systems Foundation.'
  chicago: Marchand, Mario, Su Hongyu, Emilie Morvant, Juho Rousu, and John Shawe
    Taylor. “Multilabel Structured Output Learning with Random Spanning Trees of Max-Margin
    Markov Networks.” In <i>Advances in Neural Information Processing Systems</i>,
    Vol. 27. Neural Information Processing Systems Foundation, 2014.
  ieee: M. Marchand, S. Hongyu, E. Morvant, J. Rousu, and J. Shawe Taylor, “Multilabel
    structured output learning with random spanning trees of max-margin Markov networks,”
    in <i>Advances in Neural Information Processing Systems</i>, Montreal, Canada,
    2014, vol. 27.
  ista: 'Marchand M, Hongyu S, Morvant E, Rousu J, Shawe Taylor J. 2014. Multilabel
    structured output learning with random spanning trees of max-margin Markov networks.
    Advances in Neural Information Processing Systems. NIPS: Neural Information Processing
    Systems vol. 27.'
  mla: Marchand, Mario, et al. “Multilabel Structured Output Learning with Random
    Spanning Trees of Max-Margin Markov Networks.” <i>Advances in Neural Information
    Processing Systems</i>, vol. 27, Neural Information Processing Systems Foundation,
    2014.
  short: M. Marchand, S. Hongyu, E. Morvant, J. Rousu, J. Shawe Taylor, in:, Advances
    in Neural Information Processing Systems, Neural Information Processing Systems
    Foundation, 2014.
conference:
  end_date: 2014-12-13
  location: Montreal, Canada
  name: 'NIPS: Neural Information Processing Systems'
  start_date: 2014-12-08
date_created: 2018-12-11T11:55:26Z
date_published: 2014-01-01T00:00:00Z
date_updated: 2026-06-18T18:24:19Z
day: '01'
ddc:
- '000'
department:
- _id: ChLa
intvolume: '        27'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://hal.archives-ouvertes.fr/hal-01065586
month: '01'
oa: 1
oa_version: Published Version
publication: Advances in Neural Information Processing Systems
publication_identifier:
  isbn:
  - '9781510800410'
publication_status: published
publisher: Neural Information Processing Systems Foundation
publist_id: '4996'
status: public
title: Multilabel structured output learning with random spanning trees of max-margin
  Markov networks
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 27
year: '2014'
...