A new architecture of photonic ATM switches. - Makoto Nishio; Shuji Suzuki; Kazuo Takagi; Ichiro Ogura; Takahiro Numai; Kenichi Kasahara; Kazuhisa Kaede (IEEE Commun. Mag., 1993)

Optical cross-connect system incorporated with newly developed operation and management system. - Tatsuya Shiragaki; Naoya Henmi; Tomoaki Kato; Masahiko Fujiwara; Masatoshi Misono; Takahiro Shiozawa; Shuji Suzuki (IEEE J. Sel. Areas Commun., 1998)

A 1.2-W single-chip MPEG2 MP@ML video encoder LSI including wide search range (H±288, V: ±96) motion estimation and 81-MOPS controller. - Eiji Ogura; Masatoshi Takashima; Daisuke Hiranaka; Toshiro Ishikawa; Yukio Yanagita; Shuji Suzuki; Tokuya Fukuda; Toshiyuki Ishii (IEEE J. Solid State Circuits, 1998)

A 3D visualization system for structured overlays. - Hiroya Nagao; Shuji Suzuki; Kazuyuki Shudo (Peer-to-Peer Computing, 2011)

Poster: An Ultra-Fast Computing Pipeline for Metagenome Analysis with Next-Generation DNA Sequencers. - Shuji Suzuki (SC Companion, 2012)

An Ultra-Fast Computing Pipeline for Metagenome Analysis with Next-Generation DNA Sequencers. - Shuji Suzuki; Takashi Ishida 002; Yutaka Akiyama (SC Companion, 2012)

MEGADOCK-GPU: Acceleration of Protein-Protein Docking Calculation on GPUs. - Takehiro Shimoda; Takashi Ishida 002; Shuji Suzuki; Masahito Ohue; Yutaka Akiyama (BCB, 2013)

MEGADOCK 4.0: an ultra-high-performance protein-protein docking software for heterogeneous supercomputers. - Masahito Ohue; Takehiro Shimoda; Shuji Suzuki; Yuri Matsuzaki; Takashi Ishida 002; Yutaka Akiyama (Bioinform., 2014)

Extreme Big Data (EBD): Next Generation Big Data Infrastructure Technologies Towards Yottabyte/Year. - Satoshi Matsuoka; Hitoshi Sato; Osamu Tatebe; Michihiro Koibuchi; Ikki Fujiwara; Shuji Suzuki; Masanori Kakuta; Takashi Ishida 002; Yutaka Akiyama; Toyotaro Suzumura; Koji Ueno; Hiroki Kanezashi; et al. (Supercomput. Front. Innov., 2014)

Faster sequence homology searches by clustering subsequences. - Shuji Suzuki; Masanori Kakuta; Takashi Ishida 002; Yutaka Akiyama (Bioinform., 2015)

Protein-protein docking on hardware accelerators: comparison of GPU and MIC architectures. - Takehiro Shimoda; Shuji Suzuki; Masahito Ohue; Takashi Ishida 002; Yutaka Akiyama (BMC Syst. Biol., 2015)

Single-View Performance Monitoring of On-Line Applications Running on a Cloud. - Yasuhiko Kanemasa; Shuji Suzuki; Atsushi Kubota; Junichi Higuchi (CLOUD, 2017)

ChainerMN: Scalable Distributed Deep Learning Framework. - Takuya Akiba; Keisuke Fukuda; Shuji Suzuki (CoRR, 2017)

Extremely Large Minibatch SGD: Training ResNet-50 on ImageNet in 15 Minutes. - Takuya Akiba; Shuji Suzuki; Keisuke Fukuda (CoRR, 2017)

PFDet: 2nd Place Solution to Open Images Challenge 2018 Object Detection Track. - Takuya Akiba; Tommi Kerola; Yusuke Niitani; Toru Ogawa; Shotaro Sano; Shuji Suzuki (CoRR, 2018)

Sampling Techniques for Large-Scale Object Detection From Sparsely Annotated Objects. - Yusuke Niitani; Takuya Akiba; Tommi Kerola; Toru Ogawa; Shotaro Sano; Shuji Suzuki (CVPR, 2019)

An Inductive Transfer Learning Approach using Cycle-consistent Adversarial Domain Adaptation with Application to Brain Tumor Segmentation. - Yuta Tokuoka; Shuji Suzuki; Yohei Sugawara (ICBBE, 2019)

Chainer: A Deep Learning Framework for Accelerating the Research Cycle. - Seiya Tokui; Ryosuke Okuta; Takuya Akiba; Yusuke Niitani; Toru Ogawa; Shunta Saito; Shuji Suzuki; Kota Uenishi; Brian Vogel; Hiroyuki Yamazaki Vincent (KDD, 2019)

Team PFDet's Methods for Open Images Challenge 2019. - Yusuke Niitani; Toru Ogawa; Shuji Suzuki; Takuya Akiba; Tommi Kerola; Kohei Ozaki; Shotaro Sano (CoRR, 2019)

Online-Codistillation Meets LARS, Going beyond the Limit of Data Parallelism in Deep Learning. - Shogo Murai; Hiroaki Mikami; Masanori Koyama; Shuji Suzuki; Takuya Akiba (DLS@SC, 2020)

A Scaling Law for Synthetic-to-Real Transfer: A Measure of Pre-Training. - Hiroaki Mikami; Kenji Fukumizu; Shogo Murai; Shuji Suzuki; Yuta Kikuchi; Taiji Suzuki; Shin-ichi Maeda; Kohei Hayashi (CoRR, 2021)

A Scaling Law for Syn2real Transfer: How Much Is Your Pre-training Effective? - Hiroaki Mikami; Kenji Fukumizu; Shogo Murai; Shuji Suzuki; Yuta Kikuchi; Taiji Suzuki; Shin-ichi Maeda; Kohei Hayashi (ECML/PKDD (3), 2022)

PLaMo-100B: A Ground-Up Language Model Designed for Japanese Proficiency. - Kenshin Abe; Kaizaburo Chubachi; Yasuhiro Fujita 001; Yuta Hirokawa; Kentaro Imajo; Toshiki Kataoka; Hiroyoshi Komatsu; Hiroaki Mikami; Tsuguo Mogami; Shogo Murai; Kosuke Nakago; Daisuke Nishino; et al. (CoRR, 2024)

A Judge-free LLM Open-ended Generation Benchmark Based on the Distributional Hypothesis. - Kentaro Imajo; Masanori Hirano 001; Shuji Suzuki; Hiroaki Mikami (CoRR, 2025)