---
_id: '2520'
abstract:
- lang: eng
  text: "We propose a probabilistic model to infer supervised latent variables in\r\nthe
    Hamming space from observed data. Our model allows simultaneous\r\ninference of
    the number of binary latent variables, and their values. The\r\nlatent variables
    preserve neighbourhood structure of the data in a sense\r\nthat objects in the
    same semantic concept have similar latent values, and\r\nobjects in different
    concepts have dissimilar latent values. We formulate\r\nthe supervised infinite
    latent variable problem based on an intuitive\r\nprinciple of pulling objects
    together if they are of the same type, and\r\npushing them apart if they are not.
    We then combine this principle with a\r\nflexible Indian Buffet Process prior
    on the latent variables. We show that\r\nthe inferred supervised latent variables
    can be directly used to perform a\r\nnearest neighbour search for the purpose
    of retrieval.  We introduce a new\r\napplication of dynamically extending hash
    codes, and show how to\r\neffectively couple the structure of the hash codes with
    continuously\r\ngrowing structure of the neighbourhood preserving infinite latent
    feature\r\nspace."
author:
- first_name: Novi
  full_name: Quadrianto, Novi
  last_name: Quadrianto
- first_name: Viktoriia
  full_name: Sharmanska, Viktoriia
  id: 2EA6D09E-F248-11E8-B48F-1D18A9856A87
  last_name: Sharmanska
  orcid: 0000-0003-0192-9308
- first_name: David
  full_name: Knowles, David
  last_name: Knowles
- first_name: Zoubin
  full_name: Ghahramani, Zoubin
  last_name: Ghahramani
citation:
  ama: 'Quadrianto N, Sharmanska V, Knowles D, Ghahramani Z. The supervised IBP: Neighbourhood
    preserving infinite latent feature models. In: <i>Proceedings of the 29th Conference
    Uncertainty in Artificial Intelligence</i>. AUAI Press; 2013:527-536.'
  apa: 'Quadrianto, N., Sharmanska, V., Knowles, D., &#38; Ghahramani, Z. (2013).
    The supervised IBP: Neighbourhood preserving infinite latent feature models. In
    <i>Proceedings of the 29th conference uncertainty in Artificial Intelligence</i>
    (pp. 527–536). Bellevue, WA, United States: AUAI Press.'
  chicago: 'Quadrianto, Novi, Viktoriia Sharmanska, David Knowles, and Zoubin Ghahramani.
    “The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models.”
    In <i>Proceedings of the 29th Conference Uncertainty in Artificial Intelligence</i>,
    527–36. AUAI Press, 2013.'
  ieee: 'N. Quadrianto, V. Sharmanska, D. Knowles, and Z. Ghahramani, “The supervised
    IBP: Neighbourhood preserving infinite latent feature models,” in <i>Proceedings
    of the 29th conference uncertainty in Artificial Intelligence</i>, Bellevue, WA,
    United States, 2013, pp. 527–536.'
  ista: 'Quadrianto N, Sharmanska V, Knowles D, Ghahramani Z. 2013. The supervised
    IBP: Neighbourhood preserving infinite latent feature models. Proceedings of the
    29th conference uncertainty in Artificial Intelligence. UAI: Uncertainty in Artificial
    Intelligence, 527–536.'
  mla: 'Quadrianto, Novi, et al. “The Supervised IBP: Neighbourhood Preserving Infinite
    Latent Feature Models.” <i>Proceedings of the 29th Conference Uncertainty in Artificial
    Intelligence</i>, AUAI Press, 2013, pp. 527–36.'
  short: N. Quadrianto, V. Sharmanska, D. Knowles, Z. Ghahramani, in:, Proceedings
    of the 29th Conference Uncertainty in Artificial Intelligence, AUAI Press, 2013,
    pp. 527–536.
conference:
  end_date: 2013-07-15
  location: Bellevue, WA, United States
  name: 'UAI: Uncertainty in Artificial Intelligence'
  start_date: 2013-07-11
date_created: 2018-12-11T11:58:09Z
date_published: 2013-07-11T00:00:00Z
date_updated: 2023-02-23T10:46:36Z
day: '11'
ddc:
- '000'
department:
- _id: ChLa
file:
- access_level: open_access
  checksum: 325f20c4b926bd74d39006b97df572bd
  content_type: application/pdf
  creator: system
  date_created: 2018-12-12T10:15:16Z
  date_updated: 2020-07-14T12:45:42Z
  file_id: '5134'
  file_name: IST-2013-137-v1+1_QuaShaKnoGha13.pdf
  file_size: 1117100
  relation: main_file
file_date_updated: 2020-07-14T12:45:42Z
has_accepted_license: '1'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Submitted Version
page: 527 - 536
publication: Proceedings of the 29th conference uncertainty in Artificial Intelligence
publication_identifier:
  isbn:
  - '9780974903996'
publication_status: published
publisher: AUAI Press
publist_id: '4381'
pubrep_id: '137'
quality_controlled: '1'
scopus_import: 1
status: public
title: 'The supervised IBP: Neighbourhood preserving infinite latent feature models'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2013'
...