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Naoki Yoshida
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2020 – today
- 2024
- [j9]Junichi Sakamoto
, Daisuke Fujimoto
High-Throughput Bilinear Pairing Processor for Server-Side FPGA Applications. IEEE Trans. Very Large Scale Integr. Syst. 32(8): 1498-1511 (2024) - [i5]Naoki Yoshida, Shogo Nakakita, Masaaki Imaizumi:
Effect of Random Learning Rate: Theoretical Analysis of SGD Dynamics in Non-Convex Optimization via Stationary Distribution. CoRR abs/2406.16032 (2024) - 2023
- [j8]Tsutomu Matsumoto, Junichi Sakamoto, Manami Suzuki, Dai Watanabe, Naoki Yoshida:
A Trial to Embed RAM Encryption Scheme in Cryptographic Programs. J. Inf. Process. 31: 700-707 (2023) - [i4]Naoki Yoshida, Sumio Watanabe:
Upper Bound of Real Log Canonical Threshold of Tensor Decomposition and its Application to Bayesian Inference. CoRR abs/2303.05731 (2023) - 2022
- [j7]Tatsuhiro Wakayama
Versatile cleaning service robot based on a mobile manipulator with tool switching for liquids and garbage removal in restrooms. Adv. Robotics 36(17-18): 967-981 (2022) - [c9]Zihao Song, Junichi Sakamoto, Shigeo Mitsunari, Naoki Yoshida, Riku Anzai, Tsutomu Matsumoto:
Efficient Software Implementation of GMT6-672 and GMT8-542 Pairing-Friendly Curves for a 128-Bit Security Level. ACNS Workshops 2022: 461-478 - 2021
- [j6]Manami Suzuki
Key Agreement Over Inter-Process Communication. IEEE Access 9: 137367-137383 (2021) - [c8]Naoki Yoshida
Cosmic Density Field Reconstruction with a Sparsity Prior Using Images of Distant Galaxies. BDA (Astronomy, Science, and Engineering) 2021: 93-99 - [c7]Naoki Yoshida, Itsuki Noda, Toshiharu Sugawara:
Distributed Service Area Control for Ride Sharing by using Multi-Agent Deep Reinforcement Learning. ICAART (1) 2021: 101-112 - [c6]Kohji Yoshikawa, Satoshi Tanaka, Naoki Yoshida
A 400 trillion-grid Vlasov simulation on Fugaku supercomputer: large-scale distribution of cosmic relic neutrinos in a six-dimensional phase space. SC 2021: 5 - 2020
- [j5]Tsutomu Matsumoto, Ryo Miyachi, Junichi Sakamoto, Manami Suzuki, Dai Watanabe, Naoki Yoshida:
RAM Encryption Mechanism without Hardware Support. J. Inf. Process. 28: 473-480 (2020) - [c5]Naoki Yoshida, Itsuki Noda, Toshiharu Sugawara
Multi-agent Service Area Adaptation for Ride-Sharing Using Deep Reinforcement Learning. PAAMS 2020: 363-375
2010 – 2019
- 2018
- [i3]Masato Shirasaki, Naoki Yoshida, Shiro Ikeda:
Denoising Weak Lensing Mass Maps with Deep Learning. CoRR abs/1812.05781 (2018) - 2017
- [c4]Naoki Yoshida, Shingo Ata, Hiroki Nakayama
Automation of Network Operations by Cooperation between Anomaly Detections and Operation Logs. GLOBECOM 2017: 1-6 - [c3]Akisato Kimura, Ichiro Takahashi, Masaomi Tanaka, Naoki Yasuda, Naonori Ueda, Naoki Yoshida:
Single-Epoch Supernova Classification with Deep Convolutional Neural Networks. ICDCS Workshops 2017: 354-359 - [i2]Akisato Kimura, Ichiro Takahashi, Masaomi Tanaka, Naoki Yasuda, Naonori Ueda, Naoki Yoshida:
Single-epoch supernova classification with deep convolutional neural networks. CoRR abs/1711.11526 (2017) - 2016
- [i1]Tsutomu Matsumoto, Naoki Yoshida, Shumpei Nishio, Morihisa Hoga, Yasuyuki Ohyagi, Naoya Tate, Makoto Naruse:
Optical nano artifact metrics using silicon random nanostructures. CoRR abs/1605.02120 (2016) - 2015
- [c2]Naoki Yoshida
A Large Sky Survey Project and the Related Big Data Analysis. DNIS 2015: 228-230 - 2010
- [j4]Hiroshi Yoshida, Kinji Kimura, Naoki Yoshida, Junko Tanaka, Yoshihiro Miwa:
Algebraic Approaches to Underdetermined Experiments in Biology. Inf. Media Technol. 5(4): 1218-1225 (2010) - [c1]Ningping Sun, Ryo Miyazaki, Naoki Yoshida:
Complex mapping with the interpolated Julia set and Mandelbrot set. SIGGRAPH ASIA (Posters) 2010: 49:1
2000 – 2009
- 2009
- [j3]Naoki Yoshida
Supercomputer simulations of structure formation in the Universe. Comput. Phys. Commun. 180(4): 625-627 (2009) - 2007
- [j2]Mitsuru Sato, Shuichi Ino, Naoki Yoshida, Takashi Izumi, Tohru Ifukube:
Portable Pneumatic Actuator System Using MH Alloys, Employed as Assistive Devices. J. Robotics Mechatronics 19(6): 612-618 (2007) - 2002
- [j1]Naoki Yoshida, Kazuhisa Domen, Yasuharu Koike
A method for estimating torque-vector directions of shoulder muscles using surface EMGs. Biol. Cybern. 86(3): 167-177 (2002)
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last updated on 2024-12-10 21:45 CET by the dblp team
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