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Paper Abstract and Keywords
Presentation 2020-01-28 14:00
[Invited Talk] Performance Maximization of In-Memory Reinforcement Learning with Variability-Controlled Hf1-xZrxO2 Ferroelectric Tunnel Junctions
Kensuke Ota, Marina Yamaguchi (kioxia), Radu Berdan, Takao Marukame, Yoshifumi Nishi (Toshiba), Kazuhiro Matsuo, Kota Takahashi, Yuta Kamiya, Shinji Miyano, Jun Deguchi, Shosuke Fujii, Masumi Saitoh (kioxia) SDM2019-84 Link to ES Tech. Rep. Archives: SDM2019-84
Abstract (in Japanese) (See Japanese page) 
(in English) We develop strategies to maximize the performance and reliability of in-memory reinforcement learning with Hf1-xZrxO2 ferroelectric tunnel junction by structural and material engineering.
Keyword (in Japanese) (See Japanese page) 
(in English) Ferroelectric tunnel junction / Memory / Reinforcement learning / / / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 397, SDM2019-84, pp. 9-9, Jan. 2020.
Paper # SDM2019-84 
Date of Issue 2020-01-21 (SDM) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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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 SDM2019-84 Link to ES Tech. Rep. Archives: SDM2019-84

Conference Information
Committee SDM  
Conference Date 2020-01-28 - 2020-01-28 
Place (in Japanese) (See Japanese page) 
Place (in English) Kikai-Shinko-Kaikan Bldg. 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SDM 
Conference Code 2020-01-SDM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Performance Maximization of In-Memory Reinforcement Learning with Variability-Controlled Hf1-xZrxO2 Ferroelectric Tunnel Junctions 
Sub Title (in English)
Keyword(1) Ferroelectric tunnel junction  
Keyword(2) Memory  
Keyword(3) Reinforcement learning  
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1st Author's Name Kensuke Ota  
1st Author's Affiliation kioxia (kioxia)
2nd Author's Name Marina Yamaguchi  
2nd Author's Affiliation kioxia (kioxia)
3rd Author's Name Radu Berdan  
3rd Author's Affiliation Toshiba (Toshiba)
4th Author's Name Takao Marukame  
4th Author's Affiliation Toshiba (Toshiba)
5th Author's Name Yoshifumi Nishi  
5th Author's Affiliation Toshiba (Toshiba)
6th Author's Name Kazuhiro Matsuo  
6th Author's Affiliation kioxia (kioxia)
7th Author's Name Kota Takahashi  
7th Author's Affiliation kioxia (kioxia)
8th Author's Name Yuta Kamiya  
8th Author's Affiliation kioxia (kioxia)
9th Author's Name Shinji Miyano  
9th Author's Affiliation kioxia (kioxia)
10th Author's Name Jun Deguchi  
10th Author's Affiliation kioxia (kioxia)
11th Author's Name Shosuke Fujii  
11th Author's Affiliation kioxia (kioxia)
12th Author's Name Masumi Saitoh  
12th Author's Affiliation kioxia (kioxia)
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Speaker Author-1 
Date Time 2020-01-28 14:00:00 
Presentation Time 30 minutes 
Registration for SDM 
Paper # SDM2019-84 
Volume (vol) vol.119 
Number (no) no.397 
Page p.9 
#Pages
Date of Issue 2020-01-21 (SDM) 


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