---
_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: Proceedings of the 29th Conference
Uncertainty in Artificial Intelligence. AUAI Press; 2013:527-536.'
apa: 'Quadrianto, N., Sharmanska, V., Knowles, D., & Ghahramani, Z. (2013).
The supervised IBP: Neighbourhood preserving infinite latent feature models. In
Proceedings of the 29th conference uncertainty in Artificial Intelligence
(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 Proceedings of the 29th Conference Uncertainty in Artificial Intelligence,
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 Proceedings
of the 29th conference uncertainty in Artificial Intelligence, 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.” Proceedings of the 29th Conference Uncertainty in Artificial
Intelligence, 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'
...