Satoshi Takabe

Takashi Abe

IEEE Wirel. Commun. Lett., March, 2024

Accelerating Convergence of Stein Variational Gradient Descent via Deep Unfolding.

[BibT_eX]

[DOI]

Yuya Kawamura

CoRR, 2024

Convergence Acceleration of Markov Chain Monte Carlo-based Gradient Descent by Deep Unfolding.

[BibT_eX]

[DOI]

Ryo Hagiwara

CoRR, 2024

2023

Proximal Decoding for LDPC Codes.

[BibT_eX]

[DOI]

IEICE Trans. Fundam. Electron. Commun. Comput. Sci., March, 2023

Deep Unfolded Simulated Bifurcation for Massive MIMO Signal Detection.

[BibT_eX]

[DOI]

CoRR, 2023

Hypergraph Embedding Based on Random Walk with Adjusted Transition Probabilities.

[BibT_eX]

[DOI]

Kazuya Nagasato

Kazuyuki Shudo

Proceedings of the Big Data Analytics and Knowledge Discovery, 2023

2022

Convergence Acceleration via Chebyshev Step: Plausible Interpretation of Deep-Unfolded Gradient Descent.

[BibT_eX]

[DOI]

IEICE Trans. Fundam. Electron. Commun. Comput. Sci., August, 2022

Asymptotic Mean Squared Error of Noisy Periodical Successive Over-Relaxation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2022

2021

Chebyshev Periodical Successive Over-Relaxation for Accelerating Fixed-Point Iterations.

[BibT_eX]

[DOI]

IEEE Signal Process. Lett., 2021

Deep-Unfolded Sparse CDMA: Multiuser Detector and Sparse Signature Design.

[BibT_eX]

[DOI]

Yuki Yamauchi

IEEE Access, 2021

Proximal Decoding for LDPC-coded Massive MIMO Channels.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2021

MSE-Optimaized Linear Transform for Noisy Fronthaul Channels in Distributed MIMO C-RAN.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2021

Refined Density Evolution Analysis of LDPC Codes for Successive Interference Cancellation.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2021

2020

Asymptotic Behavior of Spatial Coupling LDPC Coding for Compute-and-Forward Two-Way Relaying.

[BibT_eX]

[DOI]

IEEE Trans. Commun., 2020

Acceleration of Cooperative Least Mean Square via Chebyshev Periodical Successive Over-Relaxation.

[BibT_eX]

[DOI]

CoRR, 2020

Chebyshev Inertial Landweber Algorithm for Linear Inverse Problems.

[BibT_eX]

[DOI]

CoRR, 2020

Theoretical Interpretation of Learned Step Size in Deep-Unfolded Gradient Descent.

[BibT_eX]

[DOI]

CoRR, 2020

Chebyshev Inertial Iteration for Accelerating Fixed-Point Iterations.

[BibT_eX]

[DOI]

CoRR, 2020

Trainable Projected Gradient Detector for Sparsely Spread Code Division Multiple Access.

[BibT_eX]

[DOI]

Yuki Yamauchi

Proceedings of the 2020 IEEE International Conference on Communications Workshops, 2020

Complex Trainable Ista for Linear and Nonlinear Inverse Problems.

[BibT_eX]

[DOI]

Yonina C. Eldar

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Deep Unfolded Multicast Beamforming.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2020

2019

Approximation Theory for Connectivity of Ad Hoc Wireless Networks With Node Faults.

[BibT_eX]

[DOI]

IEEE Wirel. Commun. Lett., 2019

Trainable ISTA for Sparse Signal Recovery.

[BibT_eX]

[DOI]

Daisuke Ito

IEEE Trans. Signal Process., 2019

Compute-and-forward relaying with LDPC codes over QPSK scheme.

[BibT_eX]

[DOI]

Ángeles Vázquez-Castro

CoRR, 2019

Complex Field-Trainable ISTA for Linear and Nonlinear Inverse Problems.

[BibT_eX]

[DOI]

CoRR, 2019

Trainable Projected Gradient Detector for Massive Overloaded MIMO Channels: Data-Driven Tuning Approach.

[BibT_eX]

[DOI]

IEEE Access, 2019

Deep Learning-Aided Trainable Projected Gradient Decoding for LDPC Codes.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2019

Asymptotic Analysis on LDPC-BICM Scheme for Compute-and-Forward Relaying.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2019

Deep Learning-Aided Projected Gradient Detector for Massive Overloaded MIMO Channels.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Communications, 2019

2018

Trainable Projected Gradient Detector for Massive Overloaded MIMO Channels: Data-driven Tuning Approach.

[BibT_eX]

[DOI]

CoRR, 2018

Asymptotic Analysis of Spatial Coupling Coding for Compute-and-Forward Relaying.

[BibT_eX]

[DOI]

CoRR, 2018

Deep Learning-Aided Iterative Detector for Massive Overloaded MIMO Channels.

[BibT_eX]

[DOI]

Masayuki Imanishi

CoRR, 2018

Joint Quantizer Optimization based on Neural Quantizer for Sum-Product Decoder.

[BibT_eX]

[DOI]

CoRR, 2018

Large-deviation Properties of Linear-programming Computational Hardness of the Vertex Cover Problem.

[BibT_eX]

[DOI]

Alexander K. Hartmann

CoRR, 2018

k-connectivity of Random Graphs and Random Geometric Graphs in Node Fault Model.

[BibT_eX]

[DOI]

Proceedings of the International Symposium on Information Theory and Its Applications, 2018

Asymptotic Analysis on Spatial Coupling Coding for Two-Way Relay Channels.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Quantizer Optimization Based on Neural Quantizerfor Sum-Product Decoder.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2018

Connectivity of Ad Hoc Wireless Networks with Node Faults.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2018

2017

Fault Tolerance of Random Graphs with respect to Connectivity: Phase Transition in Logarithmic Average Degree.

[BibT_eX]

[DOI]

Takafumi Nakano

CoRR, 2017

An exact algorithm exhibiting RS-RSB/easy-hard correspondence for the maximum independent set problem.

[BibT_eX]

[DOI]

Jun Takahashi

CoRR, 2017

Typical Approximation Performance for Maximum Coverage Problem.

[BibT_eX]

[DOI]

Takanori Maehara

CoRR, 2017

2016

Typical Performance of Approximation Algorithms for NP-hard Problems.

[BibT_eX]

[DOI]

CoRR, 2016

Statistical-mechanical Analysis of Linear Programming Relaxation for Combinatorial Optimization Problems.

[BibT_eX]

[DOI]

CoRR, 2016

2013

Typical behavior of the linear programming method for combinatorial optimization problems: From a statistical-mechanical perspective.

[BibT_eX]

[DOI]