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ORCIDYudai Suzuki
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2020 – today
- 2024
[j3]Yudai Suzuki, Keita Yokoyama:
Searching problems above arithmetical transfinite recursion. Ann. Pure Appl. Log. 175(10): 103488 (2024)- 2023
- [j2]Atsushi Matsuo, Yudai Suzuki, Ikko Hamamura
, Shigeru Yamashita:
Enhancing VQE Convergence for Optimization Problems with Problem-Specific Parameterized Quantum Circuits. IEICE Trans. Inf. Syst. 106(11): 1772-1782 (2023) - 2022
- [i1]Tomoyuki Kubota, Yudai Suzuki, Shumpei Kobayashi, Quoc-Hoan Tran, Naoki Yamamoto, Kohei Nakajima:
Quantum Noise-Induced Reservoir Computing. CoRR abs/2207.07924 (2022) - 2021
- [c8]Yudai Suzuki, Hiroshi Yano, Rudy Raymond, Naoki Yamamoto:
Normalized Gradient Descent for Variational Quantum Algorithms. QCE 2021: 1-9 - 2020
- [j1]Yudai Suzuki, Hiroshi Yano, Qi Gao, Shumpei Uno, Tomoki Tanaka, Manato Akiyama, Naoki Yamamoto:
Analysis and synthesis of feature map for kernel-based quantum classifier. Quantum Mach. Intell. 2(1): 1-9 (2020) - [c7]Hiroshi Yano, Yudai Suzuki, Rudy Raymond, Naoki Yamamoto:
Efficient Discrete Feature Encoding for Variational Quantum Classifier. QCE 2020: 11-21 - [c6]Ryota Kuga, Yudai Suzuki, Tomoharu Nakashima:
An Automatic Team Evaluation System for RoboCup Soccer Simulation 2D. SCIS/ISIS 2020: 1-4
2010 – 2019
- 2019
- [c5]Yudai Suzuki, Tomoharu Nakashima:
On the Use of Simulated Future Information for Evaluating Game Situations. RoboCup 2019: 294-308 - [c4]Yudai Suzuki, Takuya Fukushima, Léa Thibout, Tomoharu Nakashima, Hidehisa Akiyama:
Game-Watching Should be More Entertaining: Real-Time Application of Field-Situation Prediction to a Soccer Monitor. RoboCup 2019: 439-447 - [c3]Yudai Suzuki, Tomoharu Nakashima:
Applying FOSSE Approach to Image Data for Evaluating Game Situations. SSCI 2019: 2228-2236 - 2018
- [c2]Hidehisa Akiyama, Tomoharu Nakashima, Takuya Fukushima, Jiarun Zhong, Yudai Suzuki, An Ohori:
HELIOS2018: RoboCup 2018 Soccer Simulation 2D League Champion. RoboCup 2018: 450-461 - 2017
- [c1]Yudai Suzuki, Keigo Kawaji, Amit R. Patel, Satoshi Tamura, Satoru Hayamizu:
Toward effective noise reduction for sub-Nyquist high-frame-rate MRI techniques with deep learning. APSIPA 2017: 1136-1139
Coauthor Index
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