Quantum annealing for variational Bayes inference

Issei Sato; Kenichi Kurihara; Shu Tanaka; Hiroshi Nakagawa; Seiji Miyashita

Quantum annealing for variational Bayes inference

Issei Sato^*, Kenichi Kurihara, Shu Tanaka, Hiroshi Nakagawa, Seiji Miyashita

^*この研究の対応する著者

研究成果: Conference contribution

6 被引用数 (Scopus)

抄録

This paper presents studies on a deterministic annealing algorithm based on quantum annealing for variational Bayes (QAVB) inference, which can be seen as an extension of the simulated annealing for variational Bayes (SAVB) inference. QAVB is as easy as SAVB to implement. Experiments revealed QAVB finds a better local optimum than SAVB in terms of the variational free energy in latent Dirichlet allocation (LDA).

本文言語	English
ホスト出版物のタイトル	Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, UAI 2009
ページ	479-486
ページ数	8
出版ステータス	Published - 2009
外部発表	はい
イベント	25th Conference on Uncertainty in Artificial Intelligence, UAI 2009 - Montreal, QC, Canada 継続期間: 2009 6月 18 → 2009 6月 21

Other

Other	25th Conference on Uncertainty in Artificial Intelligence, UAI 2009
国/地域	Canada
City	Montreal, QC
Period	09/6/18 → 09/6/21

ASJC Scopus subject areas

人工知能
応用数学

他のファイルとリンク

引用スタイル

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title = "Quantum annealing for variational Bayes inference",

abstract = "This paper presents studies on a deterministic annealing algorithm based on quantum annealing for variational Bayes (QAVB) inference, which can be seen as an extension of the simulated annealing for variational Bayes (SAVB) inference. QAVB is as easy as SAVB to implement. Experiments revealed QAVB finds a better local optimum than SAVB in terms of the variational free energy in latent Dirichlet allocation (LDA).",

author = "Issei Sato and Kenichi Kurihara and Shu Tanaka and Hiroshi Nakagawa and Seiji Miyashita",

year = "2009",

language = "English",

pages = "479--486",

booktitle = "Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, UAI 2009",

note = "25th Conference on Uncertainty in Artificial Intelligence, UAI 2009 ; Conference date: 18-06-2009 Through 21-06-2009",

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TY - GEN

T1 - Quantum annealing for variational Bayes inference

AU - Sato, Issei

AU - Kurihara, Kenichi

AU - Tanaka, Shu

AU - Nakagawa, Hiroshi

AU - Miyashita, Seiji

PY - 2009

Y1 - 2009

N2 - This paper presents studies on a deterministic annealing algorithm based on quantum annealing for variational Bayes (QAVB) inference, which can be seen as an extension of the simulated annealing for variational Bayes (SAVB) inference. QAVB is as easy as SAVB to implement. Experiments revealed QAVB finds a better local optimum than SAVB in terms of the variational free energy in latent Dirichlet allocation (LDA).

AB - This paper presents studies on a deterministic annealing algorithm based on quantum annealing for variational Bayes (QAVB) inference, which can be seen as an extension of the simulated annealing for variational Bayes (SAVB) inference. QAVB is as easy as SAVB to implement. Experiments revealed QAVB finds a better local optimum than SAVB in terms of the variational free energy in latent Dirichlet allocation (LDA).

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UR - http://www.scopus.com/inward/citedby.url?scp=80053140580&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:80053140580

SP - 479

EP - 486

BT - Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, UAI 2009

T2 - 25th Conference on Uncertainty in Artificial Intelligence, UAI 2009

Y2 - 18 June 2009 through 21 June 2009

ER -

Quantum annealing for variational Bayes inference

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ASJC Scopus subject areas

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