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YAMAGISHI Masao
Faculty of Science and Engineering Department of Applied Informatics
Professor
Researchmap URL
https://researchmap.jp/7000018165
Research activity information
■ Paper
- A Unified Design of Generalized Moreau Enhancement Matrix for Sparsity Aware LiGME Models
Y.Chen; M.Yamagishi; I.Yamada
IEICE Transactions on Fundamentals, 01 Aug. 2023, [Reviewed] - A Constrained LiGME Model and its Proximal Splitting Algorithm under Overall Convexity Condition
W.Yata; M.Yamagishi; I.Yamada
Journal of Applied and Numerical Optimization, 01 Aug. 2022, [Reviewed] - A Robust Canonical Polyadic Tensor Decomposition via Structured Low-Rank Matrix Approximation
R.Akema; M.Yamagishi; I.Yamada
IEICE Transactions on Fundamentals, 01 Jan. 2022, [Reviewed] - A Linearly Involved Generalized Moreau Enhancement of ℓ_{2,1}-Norm with Application to Weighted Group Sparse Classification
Y.Chen; M.Yamagishi; I.Yamada
Algorithms, 27 Oct. 2021, [Reviewed] - Approximate Simultaneous Diagonalization of Matrices via Structured Low-Rank Approximation
R.Akema; M.Yamagishi; I.Yamada
IEICE Transactions on Fundamentals, 01 Apr. 2021, [Reviewed] - Linearly Involved Generalized Moreau Enhanced Models and Their Proximal Splitting Algorithm under Overall Convexity Condition
J.Abe; M.Yamagishi; I.Yamada
Inverse Problems, 11 Feb. 2020, [Reviewed] - Quadratic programming over ellipsoids with applications to constrained linear regression and tensor decomposition
Anh-Huy Phan; Masao Yamagishi; Danilo Mandic; Andrzej Cichocki
Neural Computing and Applications, 20 Apr. 2019, [Reviewed] - Exploiting sparsity in tight-dimensional spaces for piecewise continuous signal recovery
H.Kuroda; M.Yamagishi; I.Yamada
IEEE Transactions on Signal Processing, 01 Jan. 2018, [Reviewed] - Smoothing of adaptive eigenvector extraction in nested orthogonal complement structure with minimum disturbance principle
K.Kakimoto; M.Yamagishi; I.Yamada
Multidimensional Systems and Signal Processing, 01 Jan. 2018, [Reviewed] - Nonexpansiveness of linearized augmented Lagrangian operator for hierarchical convex optimization
M.Yamagishi; I.Yamada
Inverse Problems, 01 Jan. 2017, [Reviewed] - Nonlinear acoustic echo cancellation by exact-online adaptive alternating minimization
H.Kuroda; M.Yamagishi; I.Yamada
IEICE Transactions on Fundamentals, 01 Jan. 2016, [Reviewed] - Graph signal denoising via trilateral filter on graph spectral domain
M.Onuki; S.Ono; M.Yamagishi; Y.Tanaka
IEEE Transactions on Signal and Information Processing over Networks, 01 Jan. 2016, [Reviewed] - Active data selection for motor imagery EEG classification
N.Tomida; T.Tanaka; S.Ono; M.Yamagishi; H.Higashi
IEEE Transactions on Biomedical Engineering, 01 Jan. 2014, [Reviewed] - Exploiting group sparsity in nonlinear acoustic echo cancellation by adaptive proximal forward-backward splitting
H.Kuroda; S.Ono; M.Yamagishi; I.Yamada
IEICE Transactions on Fundamentals, 01 Jan. 2013, [Reviewed] - Over-relaxation of the fast iterative shrinkage-thresholding algorithm with variable stepsize
M.Yamagishi; I.Yamada
Inverse Problems, 01 Jan. 2011, [Reviewed] - A deep monotone approximation operator based on the best quadratic lower bound of convex functions
M.Yamagishi; I.Yamada
IEICE Transactions on Fundamentals, 01 Jan. 2008, [Reviewed]
- Optimization over the union of closed convex sets and its application to signal processing
Grant-in-Aid for Young Scientists (B)
Tokyo Institute of Technology
01 Apr. 2014 - 31 Mar. 2019 - Robust risk estimators and their minimization for signal processing
Grant-in-Aid for Research Activity Start-up
Tokyo Institute of Technology
31 Aug. 2012 - 31 Mar. 2014
