Rio Yokota
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Professor Rio Yokota is a faculty member at Tokyo Institute of Technology, Japan. His research areas encompass quantum turbulence, high-performance computing, matrix multiplication optimization, and decentralized learning methodologies. Recent publications include studies on superfluid dynamics, parallel algorithms for GPUs, and advancements in large-scale deep learning techniques.
Recent Grants
Grant: Close
Fast and accurate eigenvalue calculations by hierarchical low-rank approximation and its application to large-scale electronic structure calculations
Open Date: 2022-04-01
Close Date: 2025-03-01
Grant: Open
A new Bayes-Duality principle for adaptive, robust, and life-long learning of AI
Open Date: 2021-10-01
Close Date: 2027-03-01
Grant: Close
Construction of Numerical Linear Algebra Based on Lattice H Matrix and High Performance Implementation on Modern Architectures
Open Date: 2021-04-01
Close Date: 2024-03-01
Grant: Close
Life-Long Deep Learning using Bayesian Principles
Open Date: 2020-04-01
Close Date: 2023-03-01
Grant: Close
Application of unconventional linear algebra technology to continuous learning of super-giant neural networks
Open Date: 2020-04-01
Close Date: 2023-03-01
Articles (9)
Collaborators (4)
Katsuhisa Ozaki
Shibaura Institute of Technology
George Bosilca
University of Tennessee
Lorena Barba
Professor
George Washington University
Noboru Harada
Head of Media Information Laboratory
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