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All Technical Committee Conferences (Searched in: All Years)
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Search Results: Conference Papers |
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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