21 Result(s)
within
Chapter
Tetsuya Sakurai
English
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Chapter
Numerical Analysis for Data Relationship
In recent years, a vast amount of data has been accumulated across various fields in industry and academia, and with the rise of artificial intelligence and machine learning technologies, knowledge discovery a...
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Chapter and Conference Paper
Image Data Recoverability Against Data Collaboration and Its Countermeasure
The development machine learning and related techniques has accelerated the use of data in a variety of fields, including medicine, finance, and advertising. Because the amount of data is increasing extremely ...
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Chapter and Conference Paper
Accelerating the Backpropagation Algorithm by Using NMF-Based Method on Deep Neural Networks
Backpropagation (BP) is the most widely used algorithm for the training of deep neural networks (DNN) and is also considered a de facto standard algorithm. However, the BP algorithm often requires a lot of com...
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Chapter and Conference Paper
Collaborative Data Analysis: Non-model Sharing-Type Machine Learning for Distributed Data
This paper proposes a novel non-model sharing-type collaborative learning method for distributed data analysis, in which data are partitioned in both samples and features. Analyzing these types of distributed ...
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Chapter and Conference Paper
Parameter Evolution Self-Adaptive Strategy and Its Application for Cuckoo Search
Cuckoo Search (CS) is a simple yet efficient swarm intelligence algorithm based on Lévy Flight. However, its performance can depend heavily on the parameter settings. Though many studies have designed control ...
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Chapter and Conference Paper
ESSEX: Equip** Sparse Solvers For Exascale
The ESSEX project has investigated programming concepts, data structures, and numerical algorithms for scalable, efficient, and robust sparse eigenvalue solvers on future heterogeneous exascale systems. Starti...
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Chapter
Scalable Eigen-Analysis Engine for Large-Scale Eigenvalue Problems
Our project aims to develop a massively parallel Eigen-Supercomputing Engine for post-petascale systems. Our Eigen-Engines are based on newly designed algorithms that are suited to the hierarchical architectur...
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Chapter and Conference Paper
Structure-Preserving Technique in the Block SS–Hankel Method for Solving Hermitian Generalized Eigenvalue Problems
The block SS–Hankel method is one of the most efficient methods for solving interior generalized eigenvalue problems (GEPs) when only the eigenvalues are required. However, even if the target GEP is Hermitian,...
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Chapter and Conference Paper
Numerical Integral Eigensolver for a Ring Region on the Complex Plane
In the present paper, we propose an extension of the Sakurai-Sugiura projection method (SSPM) for a circumference region on the complex plane. The SSPM finds eigenvalues in a specified region on the complex pl...
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Chapter and Conference Paper
Eigenspectrum Calculation of the O(a)-Improved Wilson-Dirac Operator in Lattice QCD Using the Sakurai-Sugiura Method
We have developed a computer code to find eigenvalues and eigenvectors of non-Hermitian sparse matrices arising in lattice quantum chromodynamics (lattice QCD). The Sakurai-Sugiura (SS) method (Sakurai and Sug...
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Chapter and Conference Paper
Highly Parallel Computation of Generalized Eigenvalue Problem in Vibration for Automatic Transmission of Vehicles Using the Sakurai–Sugiura Method and Supercomputers
In this paper, we discuss highly parallel computational approach for solving eigenvalue problems arising from problem in automatic of vehicles. Vibration performance is an important quality measure of vehi...
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Chapter and Conference Paper
Memory-Saving Technique for the Sakurai–Sugiura Eigenvalue Solver Using the Shifted Block Conjugate Gradient Method
In recent years, a numerical quadrature-based sparse eigensolver—the so-called Sakurai–Sugiura method—and its variants have attracted attention because of their highly coarse-grained parallelism. In this paper...
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Chapter and Conference Paper
An Error Resilience Strategy of a Complex Moment-Based Eigensolver
Recently, complex moment-based eigensolvers have been actively developed in highly parallel environments to solve large and sparse eigenvalue problems. In this paper, we provide an error resilience strategy of...
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Chapter and Conference Paper
Alternating Optimization Method Based on Nonnegative Matrix Factorizations for Deep Neural Networks
The backpropagation algorithm for calculating gradients has been widely used in computation of weights for deep neural networks (DNNs). This method requires derivatives of objective functions and has some diff...
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Chapter and Conference Paper
Efficient Algorithm for Linear Systems Arising in Solutions of Eigenproblems and Its Application to Electronic-Structure Calculations
We consider an eigenproblem derived from first-principles electronic-structure calculations. Eigensolvers based on a rational filter require solutions of linear systems with multiple shifts and multiple right ...
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Chapter and Conference Paper
On Single Precision Preconditioners for Krylov Subspace Iterative Methods
Large sparse linear systems Ax= b arise in many scientific applications. Krylov subspace iterative methods are often used for solving such linear systems. Preconditioning techniques are efficient to reduce the nu...
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Chapter and Conference Paper
A Master-Worker Type Eigensolver for Molecular Orbital Computations
We consider a parallel method for solving generalized eigenvalue problems that arise from molecular orbital computations. We use a moment-based method that finds several eigenvalues and their corresponding eig...
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Chapter and Conference Paper
A Parallel Method for Large Sparse Generalized Eigenvalue Problems by OmniRPC in a Grid Environment
In this paper we present a parallel method for finding several eigenvalues and eigenvectors of a generalized eigenvalue problem A x = λB x, where A and B are ...
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Chapter and Conference Paper
A Hybrid Parallel Method for Large Sparse Eigenvalue Problems on a Grid Computing Environment Using Ninf-G/MPI
In the present paper, we propose a hybrid parallel method for large sparse eigenvalue problems in a grid computing environment. A moment-based method that finds several eigenvalues and their corresponding eige...
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Chapter and Conference Paper
Performance Improvement by Data Management Layer in a Grid RPC System
A grid RPC system provides a useful and intuitive programming interface for master-worker type applications in a grid environment. In many grid applications, such as parameter search programs, both master and ...
