World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
34
Citations
6971
World Ranking
2864
National Ranking
47

Engineering and Technology

D-Index
34
Citations
6782
World Ranking
9134
National Ranking
202

Research.com Recognitions

  • 2015 - IEEE Fellow For contributions to inverse problems and learning in signal processing

Overview

Isao Yamada is affiliated with the Tokyo Institute of Technology in Japan. Their research contributions span several interconnected scientific fields with a strong emphasis on engineering, computer science, and mathematics.

The scientist's main fields of study include:

  • Engineering
  • Computer Science
  • Mathematics

Within these fields, they have focused on several subfields, particularly:

  • Computational Mechanics
  • Computational Theory and Mathematics
  • Numerical Analysis
  • Computer Vision and Pattern Recognition
  • Signal Processing

The primary topics explored by Isao Yamada cover areas such as:

  • Sparse and Compressive Sensing Techniques
  • Advanced Optimization Algorithms Research
  • Optimization and Variational Analysis
  • Structural Health Monitoring Techniques
  • Face and Expression Recognition
  • Blind Source Separation Techniques
  • Control Systems and Identification

Yamada has published extensively in several reputable venues, including:

  • arXiv (Cornell University)
  • IEEE Transactions on Signal Processing
  • IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences
  • 2022 30th European Signal Processing Conference (EUSIPCO)
  • Optimization

Some recent representative papers authored or co-authored by Yamada include:

  • "A constrained LiGME model and its proximal splitting algorithm under overall convexity condition" (2022), Journal of Applied and Numerical Optimization
  • "Linearly-Involved Moreau-Enhanced-Over-Subspace Model: Debiased Sparse Modeling and Stable Outlier-Robust Regression" (2023), IEEE Transactions on Signal Processing
  • "Linearly-involved Moreau-Enhanced-over-Subspace Model: Debiased Sparse Modeling and Stable Outlier-Robust Regression" (2022), arXiv (Cornell University)
  • "Stable Robust Regression under Sparse Outlier and Gaussian Noise" (2022), 2022 30th European Signal Processing Conference (EUSIPCO)
  • "A Unified Framework for Solving a General Class of Nonconvexly Regularized Convex Models" (2023), IEEE Transactions on Signal Processing

The scientist has collaborated frequently with several researchers, including:

  • Masao Yamagishi
  • Yi Zhang
  • Keita Kume
  • Wataru Yata
  • Masahiro Yukawa

Yamada was recognized with the IEEE Fellow award in 2015 for contributions to inverse problems and learning in signal processing.

Best Publications

  • Tensor completion and low-n-rank tensor recovery via convex optimization

    Silvia Gandy;Benjamin Recht;Isao Yamada

  • The Hybrid Steepest Descent Method for the Variational Inequality Problem over the Intersection of Fixed Point Sets of Nonexpansive Mappings

    Isao Yamada

  • Diffusion Least-Mean Squares With Adaptive Combiners: Formulation and Performance Analysis

    N Takahashi;I Yamada;A H Sayed

  • Hybrid Steepest Descent Method for Variational Inequality Problem over the Fixed Point Set of Certain Quasi-nonexpansive Mappings

    Isao Yamada;Nobuhiko Ogura

  • Adaptive Learning in a World of Projections

    Sergios Theodoridis;Konstantinos Slavakis;Isao Yamada

  • Minimizing certain convex functions over the intersection of the fixed point sets of nonexpansive mappings

    F. Deutsch;I. Yamada

  • Adaptive Projected Subgradient Method for Asymptotic Minimization of Sequence of Nonnegative Convex Functions

    Isao Yamada;Nobuhiko Ogura

  • An efficient robust adaptive filtering algorithm based on parallel subgradient projection techniques

    I. Yamada;K. Slavakis;K. Yamada

  • Online Kernel-Based Classification Using Adaptive Projection Algorithms

    K. Slavakis;S. Theodoridis;I. Yamada

  • Cartoon-Texture Image Decomposition Using Blockwise Low-Rank Texture Characterization

    Shunsuke Ono;Takamichi Miyata;Isao Yamada

  • A Use of Conjugate Gradient Direction for the Convex Optimization Problem over the Fixed Point Set of a Nonexpansive Mapping

    Hideaki Iiduka;Isao Yamada

  • Compositions and convex combinations of averaged nonexpansive operators

    Patrick L. Combettes;Isao Yamada

  • Minimizing the Moreau Envelope of Nonsmooth Convex Functions over the Fixed Point Set of Certain Quasi-Nonexpansive Mappings

    Isao Yamada;Masahiro Yukawa;Masao Yamagishi

  • A sparse adaptive filtering using time-varying soft-thresholding techniques

    Yukihiro Murakami;Masao Yamagishi;Masahiro Yukawa;Isao Yamada

  • A numerically robust hybrid steepest descent method for the convexly constrained generalized inverse problems

    I. Yamada

  • Robust Wideband Beamforming by the Hybrid Steepest Descent Method

    K. Slavakis;I. Yamada

  • Quadratic optimization of fixed points of nonexpansive mappings in Hilbert space

    Isao Yamada;Nobuhiko Ogura;Kohichi Sakaniwa

  • The Adaptive Projected Subgradient Method over the Fixed Point Set of Strongly Attracting Nonexpansive Mappings

    Konstantinos Slavakis;Isao Yamada;Nobuhiko Ogura

  • A subgradient-type method for the equilibrium problem over the fixed point set and its applications

    Hideaki Iiduka;Isao Yamada

  • An Adaptive Projected Subgradient Approach to Learning in Diffusion Networks

    R.L.G. Cavalcante;I. Yamada;B. Mulgrew

Frequent Co-Authors

Sergios Theodoridis
Sergios Theodoridis National and Kapodistrian University of Athens
Ali H. Sayed
Ali H. Sayed École Polytechnique Fédérale de Lausanne
R.C. de Lamare
R.C. de Lamare Pontifical Catholic University of Rio de Janeiro
Bernard Mulgrew
Bernard Mulgrew University of Edinburgh
Sergio Barbarossa
Sergio Barbarossa Sapienza University of Rome
Alex Rogers
Alex Rogers University of Oxford
Patrick L. Combettes
Patrick L. Combettes North Carolina State University
Nicholas R. Jennings
Nicholas R. Jennings Loughborough University
Benjamin Recht
Benjamin Recht University of California, Berkeley

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