Yoshitomo Matsubara

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 28

Top Topics

Adjacent Pixels

Computing Systems

Question Answering

Top Venues

Publications

Shivanshu Gupta, Yoshitomo Matsubara, Ankit Chadha, Alessandro Moschitti
Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages. ACL (Findings) (2023)
Florian Lalande, Yoshitomo Matsubara, Naoya Chiba, Tatsunori Taniai, Ryo Igarashi, Yoshitaka Ushiku
A Transformer Model for Symbolic Regression towards Scientific Discovery. CoRR (2023)
Niloofar Bahadori, Yoshitomo Matsubara, Marco Levorato, Francesco Restuccia
SplitBeam: Effective and Efficient Beamforming in Wi-Fi Networks Through Split Computing. ICDCS (2023)
Yoshitomo Matsubara, Marco Levorato, Francesco Restuccia
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges. ACM Comput. Surv. 55 (5) (2023)
Niloofar Bahadori, Yoshitomo Matsubara, Marco Levorato, Francesco Restuccia
SplitBeam: Effective and Efficient Beamforming in Wi-Fi Networks Through Split Computing. CoRR (2023)
Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt
SC2 Benchmark: Supervised Compression for Split Computing. Trans. Mach. Learn. Res. 2023 (2023)
Yoshitomo Matsubara
torchdistill Meets Hugging Face Libraries for Reproducible, Coding-Free Deep Learning Studies: A Case Study on NLP. CoRR (2023)
Shivanshu Gupta, Yoshitomo Matsubara, Ankit Chadha, Alessandro Moschitti
Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages. CoRR (2023)
Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt
SC2: Supervised Compression for Split Computing. CoRR (2022)
Yoshitomo Matsubara, Davide Callegaro, Sameer Singh, Marco Levorato, Francesco Restuccia
BottleFit: Learning Compressed Representations in Deep Neural Networks for Effective and Efficient Split Computing. WoWMoM (2022)
Yoshitomo Matsubara, Luca Soldaini, Eric Lind, Alessandro Moschitti
Ensemble Transformer for Efficient and Accurate Ranking Tasks: an Application to Question Answering Systems. CoRR (2022)
Yoshitomo Matsubara, Davide Callegaro, Sameer Singh, Marco Levorato, Francesco Restuccia
BottleFit: Learning Compressed Representations in Deep Neural Networks for Effective and Efficient Split Computing. CoRR (2022)
Yoshitomo Matsubara, Luca Soldaini, Eric Lind, Alessandro Moschitti
Ensemble Transformer for Efficient and Accurate Ranking Tasks: an Application to Question Answering Systems. EMNLP (Findings) (2022)
Yoshitomo Matsubara, Naoya Chiba, Ryo Igarashi, Tatsunori Taniai, Yoshitaka Ushiku
Rethinking Symbolic Regression Datasets and Benchmarks for Scientific Discovery. CoRR (2022)
Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt
Supervised Compression for Resource-Constrained Edge Computing Systems. WACV (2022)
Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt
Supervised Compression for Resource-constrained Edge Computing Systems. CoRR (2021)
Yoshitomo Matsubara
torchdistill: A Modular, Configuration-Driven Framework for Knowledge Distillation. RRPR (2021)
Yoshitomo Matsubara, Marco Levorato, Francesco Restuccia
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges. CoRR (2021)
Yoshitomo Matsubara, Davide Callegaro, Sabur Baidya, Marco Levorato, Sameer Singh
Head Network Distillation: Splitting Distilled Deep Neural Networks for Resource-Constrained Edge Computing Systems. IEEE Access 8 (2020)
Tamanna Hossain, Robert L. Logan IV, Arjuna Ugarte, Yoshitomo Matsubara, Sean Young, Sameer Singh
COVIDLies: Detecting COVID-19 Misinformation on Social Media. NLP4COVID@EMNLP (2020)
Yoshitomo Matsubara, Marco Levorato
Neural Compression and Filtering for Edge-assisted Real-time Object Detection in Challenged Networks. CoRR (2020)
Yoshitomo Matsubara, Marco Levorato
Split Computing for Complex Object Detectors: Challenges and Preliminary Results. CoRR (2020)
Davide Callegaro, Yoshitomo Matsubara, Marco Levorato
Optimal Task Allocation for Time-Varying Edge Computing Systems with Split DNNs. GLOBECOM (2020)
Yoshitomo Matsubara
torchdistill: A Modular, Configuration-Driven Framework for Knowledge Distillation. CoRR (2020)
Yoshitomo Matsubara, Thuy Vu, Alessandro Moschitti
Reranking for Efficient Transformer-based Answer Selection. SIGIR (2020)
Yoshitomo Matsubara, Marco Levorato
Neural Compression and Filtering for Edge-assisted Real-time Object Detection in Challenged Networks. ICPR (2020)
Yoshitomo Matsubara, Sabur Baidya, Davide Callegaro, Marco Levorato, Sameer Singh
Distilled Split Deep Neural Networks for Edge-Assisted Real-Time Systems. HotEdgeVideo@MOBICOM (2019)
Yoshitomo Matsubara, Haruhiko Nishimura, Toshiharu Samura, Hiroyuki Yoshimoto, Ryohei Tanimoto
Screen Unlocking by Spontaneous Flick Reactions with One-Class Classification Approaches. ICMLA (2016)