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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 65  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
IT, EMM 2024-05-30
12:50
Chiba Chiba University (Nishi-Chiba Campus) A Study of Proximal Decoding enhanced by Deep Unfolding
Asahi Ito, Lantian Wei, Tadashi Wadayama (NIT)
 [more]
IT, EMM 2024-05-30
13:15
Chiba Chiba University (Nishi-Chiba Campus) A Study of Optical MIMO Signal Detection Circuit based on Projected Gradient Method Using Deep Unfolding
Tomoya Kuno, Tadashi Wadayama (NIT)
 [more]
SIP, IT, RCS 2024-01-18
13:15
Miyagi
(Primary: On-site, Secondary: Online)
[Invited Talk] A Revisit to Proximal Decoding for LDPC codes
Tadashi Wadayama (NiTech) IT2023-42 SIP2023-75 RCS2023-217
In this invited talk,
our proposed algorithm, {em proximal decoding}, is revisited and
some optimization-based decodi... [more]
IT2023-42 SIP2023-75 RCS2023-217
p.68
IT 2023-08-04
09:30
Kanagawa Shonan Institute of Technology
(Primary: On-site, Secondary: Online)
Deep Unfolding-based Distributed MIMO Detection
Masaya Kumagai, Ayano Nakai-Kasai, Tadashi Wadayama (NITech) IT2023-21
This paper proposes a distributed multiple-input multiple-output signal detection algorithm based on DU (deep unfolding)... [more] IT2023-21
pp.38-43
EMM, IT 2023-05-12
09:50
Kyoto Rakuyu Kaikan (Kyoto Univ. Yoshida-South Campus)
(Primary: On-site, Secondary: Online)
Relation on Unconstrained Convex Quadratic Programming between Gradient Method and Numerical Discretization of Gradient Flow
Ayano Nakai-Kasai, Tadashi Wadayama (NITech) IT2023-7 EMM2023-7
This paper proves one of the properties in terms of gradient descent method and gradient flow. For unconstrained convex ... [more] IT2023-7 EMM2023-7
pp.31-36
EMM, IT 2023-05-12
10:15
Kyoto Rakuyu Kaikan (Kyoto Univ. Yoshida-South Campus)
(Primary: On-site, Secondary: Online)
Gradient flow decoding for LDPC codes
Tadashi Wadayama, Kensho Nakajima, Ayano Nakai-Kasai (NiTech) IT2023-8 EMM2023-8
The power consumption of the integrated circuit is becoming a significant burden, particularly for large-scale signal pr... [more] IT2023-8 EMM2023-8
pp.37-42
RCS, SR, SRW
(Joint)
2023-03-02
10:50
Tokyo Tokyo Institute of Technology, and Online
(Primary: On-site, Secondary: Online)
Precoder Optimization Using Correlation among Data for Wireless Data Aggregation
Naoyuki Hayashi, Ayano Nakai-Kasai, Tadashi Wadayama (NIT) RCS2022-273
In this paper, we discuss precoder optimization in wireless data aggregation.
Formulate the problem of minimizing the ... [more]
RCS2022-273
pp.149-154
IT, RCS, SIP 2023-01-24
15:55
Gunma Maebashi Terrsa
(Primary: On-site, Secondary: Online)
Deep Unfolding-based Weighting in Distributed MIMO Detection
Masaya Kumagai, Ayano Nakai-Kasai, Tadashi Wadayama (NITech) IT2022-49 SIP2022-100 RCS2022-228
This paper proposes distributed uplink MIMO (Multiple-Input Multiple-Output) signal detection algorithms based on DU (d... [more] IT2022-49 SIP2022-100 RCS2022-228
pp.114-119
NS, SR, RCS, SeMI, RCC
(Joint)
2022-07-13
16:00
Ishikawa The Kanazawa Theatre + Online
(Primary: On-site, Secondary: Online)
Precoder Design for Over-the-Air Computation in Correlated Data Aggregation on Wireless Sensor Networks
Ayano Nakai-Kasai, Tadashi Wadayama (NITech) RCS2022-75
 [more] RCS2022-75
pp.38-43
IT, EMM 2022-05-18
13:05
Gifu Gifu University
(Primary: On-site, Secondary: Online)
Ordinary Differential Equation and Mean Squared Error Analysis for MMSE Signal Detection in MIMO Systems
Ayano Nakai-Kasai, Tadashi Wadayama (NITech) IT2022-12 EMM2022-12
(To be available after the conference date) [more] IT2022-12 EMM2022-12
pp.61-66
IT, ISEC, RCC, WBS 2022-03-11
12:00
Online Online A study of distributed MIMO signal detection based on deep unfolding
Masaya Kumagai, Ayano Nakai-Kasai, Tadashi Wadayama (NITech) IT2021-113 ISEC2021-78 WBS2021-81 RCC2021-88
This paper proposes distributed MIMO (Multiple-Input Multiple-Output)
signal detection algorithms based on DU (deep un... [more]
IT2021-113 ISEC2021-78 WBS2021-81 RCC2021-88
pp.174-179
RCS, SIP, IT 2022-01-20
11:45
Online Online Noisy average consensus as Gaussian MAC channels
Tadashi Wadayama (Nitech) IT2021-37 SIP2021-45 RCS2021-205
 [more] IT2021-37 SIP2021-45 RCS2021-205
pp.51-56
RCS, SIP, IT 2022-01-21
11:20
Online Online Deep-Unfolded Sparse Signal Recovery Algorithm using TopK Operator
Masanari Mizutani (NITech), Satoshi Takabe (TITech), Tadashi Wadayama (NITech) IT2021-72 SIP2021-80 RCS2021-240
Compressed sensing for estimating sparse signals is formulated as an NP-hard problem, where LASSO based on convex relax... [more] IT2021-72 SIP2021-80 RCS2021-240
pp.245-251
IT 2021-07-09
13:50
Online Online Projected gradient MIMO signal detection using Chebyshev step
Asahi Mizukoshi, Tadashi Wadayama, Satoshi Takabe (NITech) IT2021-25
This paper proposes a projected gradient detection method using the Chebyshev steps for a signal detector in a MIMO (Mul... [more] IT2021-25
pp.57-62
IT 2021-07-09
14:30
Online Online Construction of Dimension Reduction Matrix for Signal Recovery of Multivariate Gaussian Vectors
Kento Yokoyama, Tadashi Wadayama, Satoshi Takabe (NIT) IT2021-26
In compressed sensing, we discuss the problem of estimating the sparse original signal $¥bm{x} ¥in ¥mathbb{R}^n$ from th... [more] IT2021-26
pp.63-68
EMM, IT 2021-05-21
10:40
Online Online Proximal Decoding for LDPC-coded Massive MIMO Channels
Tadashi Wadayama, Satoshi Takabea (Nitech) IT2021-9 EMM2021-9
 [more] IT2021-9 EMM2021-9
pp.48-53
IT 2020-09-04
10:05
Online Online A Study on Complex-valued Sparse CDMA Detection Using Deep Learning Technique
Yuki Yamauchi, Satoshi Takabe, Tadashi Wadayama (NITech) IT2020-20
 [more] IT2020-20
pp.13-18
IT 2020-09-04
10:45
Online Online Chebyshev Periodical SOR Methods for Accelerating Fixed-Point Iterations
Tadashi Wadayama, Satoshi Takabe (NiTech) IT2020-21
 [more] IT2020-21
pp.19-24
SIP 2020-08-28
10:55
Online Online Theoretical Analysis on Convergence Acceleration of Deep-Unfolded Gradient Descent
Satoshi Takabe, Tadashi Wadayama (NITech) SIP2020-35
Deep unfolding is a promising deep learning technique whose network architecture is based on existing iterative algorith... [more] SIP2020-35
pp.25-30
IT 2020-07-16
14:20
Online Online A Study on Trainable ISTA using Auto Encoder as Shrinkage Function for Image Recovery
Kento Yokoyama, Satoshi Takabe, Tadashi Wadayama (NIT) IT2020-13
ISTA (Iterative Shrinkage-Thresholding Algorithm) is one of the basic algorithms used in compressed sensing to estimate ... [more] IT2020-13
pp.13-18
 Results 1 - 20 of 65  /  [Next]  
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