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- Kazufumi Ito

Discipline name
D-index
D-index (Discipline H-index) only includes papers and citation values for an examined
discipline in contrast to General H-index which accounts for publications across all
disciplines.
Citations
Publications
World Ranking
National Ranking

Mathematics
D-index
53
Citations
12,892
256
World Ranking
653
National Ranking
336

Engineering and Technology
D-index
53
Citations
12,860
243
World Ranking
1672
National Ranking
661

- Mathematical analysis
- Algebra
- Partial differential equation

His scientific interests lie mostly in Mathematical analysis, Mathematical optimization, Optimal control, Convergence and Augmented Lagrangian method. Many of his research projects under Mathematical analysis are closely connected to Level set method with Level set method, tying the diverse disciplines of science together. Kazufumi Ito has researched Mathematical optimization in several fields, including Algorithm and Newton's method.

Kazufumi Ito interconnects Nonlinear control, Active set method, Finite element method and Applied mathematics in the investigation of issues within Optimal control. His research in Convergence intersects with topics in Discretization and Numerical tests. His Augmented Lagrangian method research includes themes of Convex optimization, Lagrange multiplier, Hilbert space, Sequential quadratic programming and Rate of convergence.

- Gaussian filters for nonlinear filtering problems (1064 citations)
- The Primal-Dual Active Set Strategy as a Semismooth Newton Method (728 citations)
- Lagrange Multiplier Approach to Variational Problems and Applications (406 citations)

His main research concerns Mathematical analysis, Mathematical optimization, Applied mathematics, Optimal control and Control theory. His research is interdisciplinary, bridging the disciplines of Convergence and Mathematical analysis. Kazufumi Ito combines subjects such as Regularization and Inverse problem with his study of Mathematical optimization.

His work on Nonlinear system expands to the thematically related Applied mathematics. His research in Optimal control focuses on subjects like Newton's method, which are connected to Algorithm. His studies deal with areas such as Navier–Stokes equations and Finite element method as well as Control theory.

- Mathematical analysis (35.25%)
- Mathematical optimization (23.74%)
- Applied mathematics (20.86%)

- Mathematical optimization (23.74%)
- Algorithm (6.12%)
- Mathematical analysis (35.25%)

Kazufumi Ito mainly investigates Mathematical optimization, Algorithm, Mathematical analysis, Applied mathematics and Regularization. His work on Optimal control and Lagrange multiplier is typically connected to Bilinear control as part of general Mathematical optimization study, connecting several disciplines of science. Kazufumi Ito has researched Optimal control in several fields, including Quadratic equation and Partial differential equation.

His studies in Algorithm integrate themes in fields like Inverse, Newton's method and Robustness. Kazufumi Ito interconnects Convergence and Mixed finite element method, Domain decomposition methods, Finite element method in the investigation of issues within Mathematical analysis. The various areas that Kazufumi Ito examines in his Applied mathematics study include Hyperparameter, Inverse problem, Tikhonov regularization and Nonlinear system.

- A direct sampling method to an inverse medium scattering problem (92 citations)
- Inverse Problems: Tikhonov Theory And Algorithms (87 citations)
- A direct sampling method for inverse electromagnetic medium scattering (52 citations)

- Mathematical analysis
- Algebra
- Partial differential equation

Kazufumi Ito mostly deals with Algorithm, Mathematical optimization, Inverse, Direct sampling and Newton's method. His Algorithm research is multidisciplinary, incorporating elements of Cauchy distribution, Sampling, Type and Robustness. His study of Optimal control is a part of Mathematical optimization.

His Optimal control study combines topics from a wide range of disciplines, such as Mixed finite element method, Convergence, State, Convex analysis and Pointwise. His research integrates issues of Mathematical theory, Scattering, Inverse problem and Bellman equation in his study of Inverse. He has included themes like Artificial neural network, Feedforward neural network, Boundary value problem, Sequence and Ansatz in his Newton's method study.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Gaussian filters for nonlinear filtering problems

K. Ito;K. Xiong.

IEEE Transactions on Automatic Control **(2000)**

1740 Citations

Gaussian filter for nonlinear filtering problems

K. Ito.

conference on decision and control **(2000)**

1390 Citations

The Primal-Dual Active Set Strategy as a Semismooth Newton Method

M. Hintermüller;K. Ito;K. Kunisch.

Siam Journal on Optimization **(2002)**

1128 Citations

Lagrange multiplier approach to variational problems and applications

Kazufumi Ito;Karl Kunisch.

**(2008)**

750 Citations

The Immersed Interface Method: Numerical Solutions of PDEs Involving Interfaces and Irregular Domains

Zhilin Li;Kazufumi Ito.

**(2006)**

643 Citations

Primal-Dual Strategy for Constrained Optimal Control Problems

Maïtine Bergounioux;Kazufumi Ito;Karl Kunisch.

Siam Journal on Control and Optimization **(1999)**

378 Citations

A Reduced-Order Method for Simulation and Control of Fluid Flows

K. Ito;S.S. Ravindran.

Journal of Computational Physics **(1998)**

373 Citations

Level-set function approach to an inverse interface problem

Kazufumi Ito;Karl Kunisch;Zhilin Li.

Inverse Problems **(2001)**

257 Citations

Maximum Principle Preserving Schemes for Interface Problems with Discontinuous Coefficients

Zhilin Li;Kazufumi Ito.

SIAM Journal on Scientific Computing **(2001)**

210 Citations

The augmented lagrangian method for parameter estimation in elliptic systems

Kazufumi Ito;Karl Kunisch.

Siam Journal on Control and Optimization **(1990)**

192 Citations

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