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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
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Committee Date Time Place Paper Title / Authors Abstract Paper #
IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] 2023-02-22
09:45
Hokkaido Hokkaido Univ. Probabilistic Approach towards Theoretical Understanding for Adversarial Training
Soichiro Kumano (UTokyo), Hiroshi Kera (Chiba Univ.), Toshihiko Yamasaki (UTokyo) ITS2022-59 IE2022-76
In this paper, we provide the first theoretical analysis of the training dynamics of adversarial training of deep neural... [more] ITS2022-59 IE2022-76
pp.95-100
CCS, NLP 2019-06-07
14:45
Niigata machinaka campus nagaoka Before the Edge of Chaos -- Short-Term Memory in Echo State Networks --
Taichi Haruna (TWCU), Kohei Nakajima (Tokyo Univ.) NLP2019-23 CCS2019-6
We study short-term memory of discrete-time nonlinear recurrent neural networks driven by small input signals. We theore... [more] NLP2019-23 CCS2019-6
pp.25-29
NLP 2011-05-26
14:15
Kagawa Olive park olive memorial hall An Analysis of a High-Order Delay-Locked Loop in the Presence of White Channel Noise and Nonwhite Multiple Access Interference
Keisuke Nagata, Hisato Fujisaka, Takeshi Kamio, Kazuhisa Haeiwa (Hiroshima City Univ.) NLP2011-4
This manuscript reports a procedure and results of probabilistic analysis of non-coherent delay-locked loop (NC-DLL) use... [more] NLP2011-4
pp.15-20
NLP 2010-12-13
11:00
Tottori Yonago Convention Center An All-Coupled Probabilistic Network Model of Delay-Locked Loops
Keisuke Nagata, Hisato Fujisaka, Takeshi Kamio, Kazuhisa Haeiwa (Hiroshima City Univ.) NLP2010-115
In this paper, we build a probabilistic 2J+1-site network which is a model of a delay-locked loop (DLL) in a CDMA commun... [more] NLP2010-115
pp.21-26
AI 2004-06-21
16:25
Tokyo Kikai-Shinko-Kaikan Bldg. Accelerating Boltzmann machine
Daisuke Itoh, Keita Torii, Tomo Munehisa (Univ. of Yamanashi)
Learning in a Boltzmann machine requires a very long calculation time because of statistical averaging. In order to redu... [more] AI2004-11
pp.57-62
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