Yoshitomo Matsubara

32 papers A* 1A 3B 2C 2Journal 18Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	A Multi-Task Supervised Compression Model for Split Computing. WACV Yoshitomo Matsubara, Matteo Mendula, Marco Levorato
2025	J	`jnl`	A Multi-task Supervised Compression Model for Split Computing. CoRR Yoshitomo Matsubara, Matteo Mendula, Marco Levorato
2024	J	`jnl`	Rethinking Symbolic Regression Datasets and Benchmarks for Scientific Discovery. J. Data-centric Mach. Learn. Res. Yoshitomo Matsubara, Naoya Chiba, Ryo Igarashi, Yoshitaka Ushiku
2023	J	`jnl`	A Transformer Model for Symbolic Regression towards Scientific Discovery. CoRR Florian Lalande, Yoshitomo Matsubara, Naoya Chiba, Tatsunori Taniai, Ryo Igarashi, Yoshitaka Ushiku
2023	—	`conf`	Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages. ACL (Findings) Shivanshu Gupta, Yoshitomo Matsubara, Ankit Chadha, Alessandro Moschitti
2023	J	`jnl`	Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages. CoRR Shivanshu Gupta, Yoshitomo Matsubara, Ankit Chadha, Alessandro Moschitti
2023	J	`jnl`	SC2 Benchmark: Supervised Compression for Split Computing. Trans. Mach. Learn. Res. Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt
2023	J	`jnl`	Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges. ACM Comput. Surv. Yoshitomo Matsubara, Marco Levorato, Francesco Restuccia
2023	A	`conf`	SplitBeam: Effective and Efficient Beamforming in Wi-Fi Networks Through Split Computing. ICDCS Niloofar Bahadori, Yoshitomo Matsubara, Marco Levorato, Francesco Restuccia
2023	J	`jnl`	SplitBeam: Effective and Efficient Beamforming in Wi-Fi Networks Through Split Computing. CoRR Niloofar Bahadori, Yoshitomo Matsubara, Marco Levorato, Francesco Restuccia
2023	J	`jnl`	torchdistill Meets Hugging Face Libraries for Reproducible, Coding-Free Deep Learning Studies: A Case Study on NLP. CoRR Yoshitomo Matsubara
2022	C	`conf`	BottleFit: Learning Compressed Representations in Deep Neural Networks for Effective and Efficient Split Computing. WoWMoM Yoshitomo Matsubara, Davide Callegaro, Sameer Singh, Marco Levorato, Francesco Restuccia
2022	J	`jnl`	BottleFit: Learning Compressed Representations in Deep Neural Networks for Effective and Efficient Split Computing. CoRR Yoshitomo Matsubara, Davide Callegaro, Sameer Singh, Marco Levorato, Francesco Restuccia
2022	—	`conf`	Ensemble Transformer for Efficient and Accurate Ranking Tasks: an Application to Question Answering Systems. EMNLP (Findings) Yoshitomo Matsubara, Luca Soldaini, Eric Lind, Alessandro Moschitti
2022	J	`jnl`	Ensemble Transformer for Efficient and Accurate Ranking Tasks: an Application to Question Answering Systems. CoRR Yoshitomo Matsubara, Luca Soldaini, Eric Lind, Alessandro Moschitti
2022	J	`jnl`	Rethinking Symbolic Regression Datasets and Benchmarks for Scientific Discovery. CoRR Yoshitomo Matsubara, Naoya Chiba, Ryo Igarashi, Tatsunori Taniai, Yoshitaka Ushiku
2022	J	`jnl`	SC2: Supervised Compression for Split Computing. CoRR Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt
2022	A	`conf`	Supervised Compression for Resource-Constrained Edge Computing Systems. WACV Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt
2022	—	`—`	Towards Split Computing: Supervised Compression for Resource-Constrained Edge Computing Systems Yoshitomo Matsubara
2021	J	`jnl`	Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges. CoRR Yoshitomo Matsubara, Marco Levorato, Francesco Restuccia
2021	J	`jnl`	Supervised Compression for Resource-constrained Edge Computing Systems. CoRR Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt
2021	—	`conf`	torchdistill: A Modular, Configuration-Driven Framework for Knowledge Distillation. RRPR Yoshitomo Matsubara
2020	—	`conf`	COVIDLies: Detecting COVID-19 Misinformation on Social Media. NLP4COVID@EMNLP Tamanna Hossain, Robert L. Logan IV, Arjuna Ugarte, Yoshitomo Matsubara, Sean Young, Sameer Singh
2020	J	`jnl`	Head Network Distillation: Splitting Distilled Deep Neural Networks for Resource-Constrained Edge Computing Systems. IEEE Access Yoshitomo Matsubara, Davide Callegaro, Sabur Baidya, Marco Levorato, Sameer Singh
2020	B	`conf`	Neural Compression and Filtering for Edge-assisted Real-time Object Detection in Challenged Networks. ICPR Yoshitomo Matsubara, Marco Levorato
2020	J	`jnl`	Neural Compression and Filtering for Edge-assisted Real-time Object Detection in Challenged Networks. CoRR Yoshitomo Matsubara, Marco Levorato
2020	B	`conf`	Optimal Task Allocation for Time-Varying Edge Computing Systems with Split DNNs. GLOBECOM Davide Callegaro, Yoshitomo Matsubara, Marco Levorato
2020	A*	`conf`	Reranking for Efficient Transformer-based Answer Selection. SIGIR Yoshitomo Matsubara, Thuy Vu, Alessandro Moschitti
2020	J	`jnl`	Split Computing for Complex Object Detectors: Challenges and Preliminary Results. CoRR Yoshitomo Matsubara, Marco Levorato
2020	J	`jnl`	torchdistill: A Modular, Configuration-Driven Framework for Knowledge Distillation. CoRR Yoshitomo Matsubara
2019	—	`conf`	Distilled Split Deep Neural Networks for Edge-Assisted Real-Time Systems. HotEdgeVideo@MobiCom Yoshitomo Matsubara, Sabur Baidya, Davide Callegaro, Marco Levorato, Sameer Singh
2016	C	`conf`	Screen Unlocking by Spontaneous Flick Reactions with One-Class Classification Approaches. ICMLA Yoshitomo Matsubara, Haruhiko Nishimura, Toshiharu Samura, Hiroyuki Yoshimoto, Ryohei Tanimoto