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ORCIDKazutoshi Hirose
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2020 – today
- 2022
[c12]Yasuyuki Okoshi, Ángel López García-Arias, Kazutoshi Hirose, Kota Ando, Kazushi Kawamura, Thiem Van Chu, Masato Motomura, Jaehoon Yu:
Multicoated Supermasks Enhance Hidden Networks. ICML 2022: 17045-17055- [c11]Kazutoshi Hirose, Jaehoon Yu, Kota Ando, Yasuyuki Okoshi, Ángel López García-Arias
, Junnosuke Suzuki, Thiem Van Chu, Kazushi Kawamura, Masato Motomura:
Hiddenite: 4K-PE Hidden Network Inference 4D-Tensor Engine Exploiting On-Chip Model Construction Achieving 34.8-to-16.0TOPS/W for CIFAR-100 and ImageNet. ISSCC 2022: 1-3 - 2021
- [j4]Kazutoshi Hirose, Shinya Takamaeda-Yamazaki, Jaehoon Yu, Masato Motomura:
Selective Fine-Tuning on a Classifier Ensemble: Realizing Adaptive Neural Networks With a Diversified Multi-Exit Architecture. IEEE Access 9: 6179-6187 (2021) - [j3]Junnosuke Suzuki, Tomohiro Kaneko, Kota Ando, Kazutoshi Hirose, Kazushi Kawamura, Thiem Van Chu, Masato Motomura, Jaehoon Yu:
ProgressiveNN: Achieving Computational Scalability with Dynamic Bit-Precision Adjustment by MSB-first Accumulative Computation. Int. J. Netw. Comput. 11(2): 338-353 (2021) - [c10]Kota Ando, Jaehoon Yu, Kazutoshi Hirose, Hiroki Nakahara, Kazushi Kawamura, Thiem Van Chu, Masato Motomura:
Edge Inference Engine for Deep & Random Sparse Neural Networks with 4-bit Cartesian-Product MAC Array and Pipelined Activation Aligner. HCS 2021: 1-21 - 2020
- [c9]Junnosuke Suzuki, Kota Ando, Kazutoshi Hirose, Kazushi Kawamura, Thiem Van Chu, Masato Motomura, Jaehoon Yu:
ProgressiveNN: Achieving Computational Scalability without Network Alteration by MSB-first Accumulative Computation. CANDAR 2020: 215-220 - [c8]Kota Shiba, Tatsuo Omori, Kodai Ueyoshi, Kota Ando, Kazutoshi Hirose, Shinya Takamaeda-Yamazaki, Masato Motomura, Mototsugu Hamada, Tadahiro Kuroda:
A 3D-Stacked SRAM using Inductive Coupling with Low-Voltage Transmitter and 12: 1 SerDes. ISCAS 2020: 1-5
2010 – 2019
- 2019
- [j2]Kota Ando, Kodai Ueyoshi, Yuka Oba, Kazutoshi Hirose, Ryota Uematsu, Takumi Kudo, Masayuki Ikebe, Tetsuya Asai, Shinya Takamaeda-Yamazaki, Masato Motomura:
Dither NN: Hardware/Algorithm Co-Design for Accurate Quantized Neural Networks. IEICE Trans. Inf. Syst. 102-D(12): 2341-2353 (2019) - [j1]Kodai Ueyoshi, Kota Ando, Kazutoshi Hirose, Shinya Takamaeda-Yamazaki, Mototsugu Hamada, Tadahiro Kuroda, Masato Motomura:
QUEST: Multi-Purpose Log-Quantized DNN Inference Engine Stacked on 96-MB 3-D SRAM Using Inductive Coupling Technology in 40-nm CMOS. IEEE J. Solid State Circuits 54(1): 186-196 (2019) - 2018
- [c7]Kota Ando, Kodai Ueyoshi, Yuka Oba, Kazutoshi Hirose, Ryota Uematsu, Takumi Kudo, Masayuki Ikebe, Tetsuya Asai, Shinya Takamaeda-Yamazaki, Masato Motomura:
Dither NN: An Accurate Neural Network with Dithering for Low Bit-Precision Hardware. FPT 2018: 6-13 - [c6]Kodai Ueyoshi, Kota Ando, Kazutoshi Hirose, Shinya Takamaeda-Yamazaki, Junichiro Kadomoto, Tomoki Miyata, Mototsugu Hamada, Tadahiro Kuroda, Masato Motomura:
QUEST: A 7.49TOPS multi-purpose log-quantized DNN inference engine stacked on 96MB 3D SRAM using inductive-coupling technology in 40nm CMOS. ISSCC 2018: 216-218 - [c5]Takumi Kudo, Kodai Ueyoshi, Kota Ando, Kazutoshi Hirose, Ryota Uematsu, Yuka Oba, Masayuki Ikebe, Tetsuya Asai, Masato Motomura, Shinya Takamaeda-Yamazaki:
Area and Energy Optimization for Bit-Serial Log-Quantized DNN Accelerator with Shared Accumulators. MCSoC 2018: 237-243 - 2017
- [c4]Shinya Takamaeda-Yamazaki, Kodai Ueyoshi, Kota Ando, Ryota Uematsu, Kazutoshi Hirose, Masayuki Ikebe, Tetsuya Asai, Masato Motomura:
Accelerating deep learning by binarized hardware. APSIPA 2017: 1045-1051 - [c3]Kazutoshi Hirose, Ryota Uematsu, Kota Ando, Kentaro Orimo, Kodai Ueyoshi, Masayuki Ikebe, Tetsuya Asai, Shinya Takamaeda-Yamazaki, Masato Motomura:
Logarithmic Compression for Memory Footprint Reduction in Neural Network Training. CANDAR 2017: 291-297 - [c2]Haruyoshi Yonekawa, Shimpei Sato, Hiroki Nakahara, Kota Ando, Kodai Ueyoshi, Kazutoshi Hirose, Kentaro Orimo, Shinya Takamaeda-Yamazaki, Masayuki Ikebe, Tetsuya Asai, Masato Motomura:
In-memory area-efficient signal streaming processor design for binary neural networks. MWSCAS 2017: 116-119 - [c1]Kazutoshi Hirose, Kota Ando, Kodai Ueyoshi, Masayuki Ikebe, Tetsuya Asai, Masato Motomura, Shinya Takamaeda-Yamazaki:
Quantization Error-Based Regularization in Neural Networks. SGAI Conf. 2017: 137-142
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