Yoshitomo Matsubara

According to our database, Yoshitomo Matsubara authored at least 21 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

SC2 Benchmark: Supervised Compression for Split Computing.

Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt

Trans. Mach. Learn. Res., 2023

Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges.

Yoshitomo Matsubara, Marco Levorato, Francesco Restuccia

ACM Comput. Surv., 2023

A Transformer Model for Symbolic Regression towards Scientific Discovery.

Florian Lalande, Yoshitomo Matsubara, Naoya Chiba, Tatsunori Taniai, Ryo Igarashi, Yoshitaka Ushiku

CoRR, 2023

torchdistill Meets Hugging Face Libraries for Reproducible, Coding-Free Deep Learning Studies: A Case Study on NLP.

Yoshitomo Matsubara

CoRR, 2023

SplitBeam: Effective and Efficient Beamforming in Wi-Fi Networks Through Split Computing.

Niloofar Bahadori, Yoshitomo Matsubara, Marco Levorato, Francesco Restuccia

Proceedings of the 43rd IEEE International Conference on Distributed Computing Systems, 2023

Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages.

Shivanshu Gupta, Yoshitomo Matsubara, Ankit Chadha, Alessandro Moschitti

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

Towards Split Computing: Supervised Compression for Resource-Constrained Edge Computing Systems

Yoshitomo Matsubara

PhD thesis, 2022

Rethinking Symbolic Regression Datasets and Benchmarks for Scientific Discovery.

Yoshitomo Matsubara, Naoya Chiba, Ryo Igarashi, Tatsunori Taniai, Yoshitaka Ushiku

CoRR, 2022

SC2: Supervised Compression for Split Computing.

Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt

CoRR, 2022

BottleFit: Learning Compressed Representations in Deep Neural Networks for Effective and Efficient Split Computing.

Yoshitomo Matsubara, Davide Callegaro, Sameer Singh, Marco Levorato, Francesco Restuccia

Proceedings of the 23rd IEEE International Symposium on a World of Wireless, 2022

Supervised Compression for Resource-Constrained Edge Computing Systems.

Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Ensemble Transformer for Efficient and Accurate Ranking Tasks: an Application to Question Answering Systems.

Yoshitomo Matsubara, Luca Soldaini, Eric Lind, Alessandro Moschitti

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021

torchdistill: A Modular, Configuration-Driven Framework for Knowledge Distillation.

Yoshitomo Matsubara

Proceedings of the Reproducible Research in Pattern Recognition, 2021

2020

Split Computing for Complex Object Detectors: Challenges and Preliminary Results.

Yoshitomo Matsubara, Marco Levorato

CoRR, 2020

Head Network Distillation: Splitting Distilled Deep Neural Networks for Resource-Constrained Edge Computing Systems.

Yoshitomo Matsubara, Davide Callegaro, Sabur Baidya, Marco Levorato, Sameer Singh

IEEE Access, 2020

Reranking for Efficient Transformer-based Answer Selection.

Yoshitomo Matsubara, Thuy Vu, Alessandro Moschitti

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Neural Compression and Filtering for Edge-assisted Real-time Object Detection in Challenged Networks.

Yoshitomo Matsubara, Marco Levorato

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Optimal Task Allocation for Time-Varying Edge Computing Systems with Split DNNs.

Davide Callegaro, Yoshitomo Matsubara, Marco Levorato

Proceedings of the IEEE Global Communications Conference, 2020

COVIDLies: Detecting COVID-19 Misinformation on Social Media.

Tamanna Hossain, Robert L. Logan IV, Arjuna Ugarte, Yoshitomo Matsubara, Sean Young, Sameer Singh

Proceedings of the 1st Workshop on NLP for COVID-19@ EMNLP 2020, Online, December 2020, 2020

2019

Distilled Split Deep Neural Networks for Edge-Assisted Real-Time Systems.

Yoshitomo Matsubara, Sabur Baidya, Davide Callegaro, Marco Levorato, Sameer Singh

Proceedings of the 2019 Workshop on Hot Topics in Video Analytics and Intelligent Edges, 2019

2016

Screen Unlocking by Spontaneous Flick Reactions with One-Class Classification Approaches.

Yoshitomo Matsubara, Haruhiko Nishimura, Toshiharu Samura, Hiroyuki Yoshimoto, Ryohei Tanimoto

Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016