| Tensor completion and low-n-rank tensor recovery via convex optimization S Gandy, B Recht, I Yamada Inverse problems 27 (2), 025010, 2011 | 875 | 2011 |
| The hybrid steepest descent method for the variational inequality problem over the intersection of fixed point sets of nonexpansive mappings I Yamada Inherently parallel algorithms in feasibility and optimization and their …, 2001 | 865 | 2001 |
| Diffusion least-mean squares with adaptive combiners: Formulation and performance analysis N Takahashi, I Yamada, AH Sayed IEEE Transactions on Signal Processing 58 (9), 4795-4810, 2010 | 343 | 2010 |
| Hybrid steepest descent method for variational inequality problem over the fixed point set of certain quasi-nonexpansive mappings I Yamada, N Ogura Taylor & Francis Group 25 (7-8), 619-655, 2005 | 320 | 2005 |
| Minimizing certain convex functions over the intersection of the fixed point sets of nonexpansive mappings F Deutsch, I Yamada Numerical Functional Analysis and Optimization 19 (1), 33-56, 1998 | 266 | 1998 |
| Adaptive learning in a world of projections S Theodoridis, K Slavakis, I Yamada IEEE Signal Processing Magazine 28 (1), 97-123, 2010 | 259 | 2010 |
| Adaptive projected subgradient method for asymptotic minimization of sequence of nonnegative convex functions I Yamada, N Ogura Taylor & Francis Group 25 (7-8), 593-617, 2005 | 227 | 2005 |
| An efficient robust adaptive filtering algorithm based on parallel subgradient projection techniques I Yamada, K Slavakis, K Yamada IEEE Transactions on Signal Processing 50 (5), 1091-1101, 2002 | 165 | 2002 |
| Compositions and convex combinations of averaged nonexpansive operators PL Combettes, I Yamada Journal of Mathematical Analysis and Applications 425 (1), 55-70, 2015 | 131 | 2015 |
| Online kernel-based classification using adaptive projection algorithms K Slavakis, S Theodoridis, I Yamada IEEE Transactions on Signal Processing 56 (7), 2781-2796, 2008 | 131 | 2008 |
| Cartoon-texture image decomposition using blockwise low-rank texture characterization S Ono, T Miyata, I Yamada IEEE Transactions on Image Processing 23 (3), 1128-1142, 2014 | 129 | 2014 |
| Minimizing the Moreau envelope of nonsmooth convex functions over the fixed point set of certain quasi-nonexpansive mappings I Yamada, M Yukawa, M Yamagishi Fixed-Point Algorithms for Inverse Problems in Science and Engineering, 345-390, 2011 | 120 | 2011 |
| A use of conjugate gradient direction for the convex optimization problem over the fixed point set of a nonexpansive mapping H Iiduka, I Yamada SIAM Journal on Optimization 19 (4), 1881-1893, 2009 | 118 | 2009 |
| A sparse adaptive filtering using time-varying soft-thresholding techniques Y Murakami, M Yamagishi, M Yukawa, I Yamada 2010 IEEE International Conference on Acoustics, Speech and Signal …, 2010 | 111 | 2010 |
| Robust wideband beamforming by the hybrid steepest descent method K Slavakis, I Yamada IEEE Transactions on Signal Processing 55 (9), 4511-4522, 2007 | 108 | 2007 |
| Non-strictly convex minimization over the fixed point set of an asymptotically shrinking nonexpansive mapping N Ogura, I Yamada Taylor & Francis Group 23 (1-2), 113-137, 2002 | 100 | 2002 |
| A numerically robust hybrid steepest descent method for the convexly constrained generalized inverse problems I Yamada, N Ogura, N Shirakawa Contemporary Mathematics 313, 269-305, 2002 | 99 | 2002 |
| Quadratic optimization of fixed points of nonexpansive mappings in hubert space I Yamada, N Ogura, K Sakaniwa Numerical Functional Analysis and Optimization 19 (1-2), 165-190, 1998 | 99 | 1998 |
| The adaptive projected subgradient method over the fixed point set of strongly attracting nonexpansive mappings K Slavakis, I Yamada, N Ogura Numerical functional analysis and optimization 27 (7-8), 905-930, 2006 | 98 | 2006 |
| A subgradient-type method for the equilibrium problem over the fixed point set and its applications H Iiduka, I Yamada Optimization 58 (2), 251-261, 2009 | 86 | 2009 |
Masao YamagishiTokyo Institute of TechnologyDirección de correo verificada de sp.ss.titech.ac.jp
