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Paper Abstract and Keywords
Presentation 2023-09-08 10:55
Langevin-type algorithm for approximate sampling from distributions under non-log-concavity and non-smoothness
Shogo Nakakita (Univ. of Tokyo) IBISML2023-26
Abstract (in Japanese) (See Japanese page) 
(in English) This study proposes a Langevin-type algorithm for approximate sampling from non-log-concave non-smooth distributions with unknown normalizing constants. Provided that the discontinuity of weak gradients of the potentials is uniformly bounded and the potentials are strongly dissipative, we examine the sampling complexity of the algorithm to let the 2-Wasserstein distance between the law of the algorithm and a target distribution.
Keyword (in Japanese) (See Japanese page) 
(in English) approximate sampling / Langevin algorithm / non-log-concave non-smooth distributions / / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 186, IBISML2023-26, pp. 8-11, Sept. 2023.
Paper # IBISML2023-26 
Date of Issue 2023-09-01 (IBISML) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF IBISML2023-26

Conference Information
Committee IBISML  
Conference Date 2023-09-08 - 2023-09-08 
Place (in Japanese) (See Japanese page) 
Place (in English) Osaka Metropolitan University (Nakamozu Campus) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Machine Learning, etc. 
Paper Information
Registration To IBISML 
Conference Code 2023-09-IBISML 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Langevin-type algorithm for approximate sampling from distributions under non-log-concavity and non-smoothness 
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Keyword(1) approximate sampling  
Keyword(2) Langevin algorithm  
Keyword(3) non-log-concave non-smooth distributions  
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1st Author's Name Shogo Nakakita  
1st Author's Affiliation University of Tokyo (Univ. of Tokyo)
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Speaker Author-1 
Date Time 2023-09-08 10:55:00 
Presentation Time 25 minutes 
Registration for IBISML 
Paper # IBISML2023-26 
Volume (vol) vol.123 
Number (no) no.186 
Page pp.8-11 
#Pages 4 
Date of Issue 2023-09-01 (IBISML) 

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