--- _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' ...