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Martin Jaggi

2000–2026 年に発表

別表記
Martin Jäggi
212
論文数
25,195
被引用数
58
h 指数
133
i10 指数

被引用数

Martin Jaggi の年別被引用数1971 年: 被引用 1 件1989 年: 被引用 1 件2001 年: 被引用 7 件2002 年: 被引用 6 件2003 年: 被引用 4 件2004 年: 被引用 6 件2005 年: 被引用 3 件2006 年: 被引用 3 件2007 年: 被引用 2 件2008 年: 被引用 10 件2009 年: 被引用 7 件2010 年: 被引用 10 件2011 年: 被引用 21 件2012 年: 被引用 37 件2013 年: 被引用 43 件2014 年: 被引用 84 件2015 年: 被引用 142 件2016 年: 被引用 152 件2017 年: 被引用 224 件2018 年: 被引用 318 件2019 年: 被引用 529 件2020 年: 被引用 1,172 件2021 年: 被引用 1,803 件2022 年: 被引用 1,588 件2023 年: 被引用 1,736 件2024 年: 被引用 2,041 件2025 年: 被引用 2,074 件2026 年: 被引用 755 件1972〜1988 年は被引用が無いため表示していません1990〜2000 年は被引用が無いため表示していません

引用元

国・地域

この著者を引用した国・地域の世界地図中国: 引用元論文 2,770 件、この内訳の 23.2%アメリカ合衆国: 引用元論文 2,556 件、この内訳の 21.4%イギリス: 引用元論文 651 件、この内訳の 5.4%ドイツ: 引用元論文 436 件、この内訳の 3.6%オーストラリア: 引用元論文 382 件、この内訳の 3.2%香港: 引用元論文 376 件、この内訳の 3.1%カナダ: 引用元論文 366 件、この内訳の 3.1%フランス: 引用元論文 365 件、この内訳の 3%スイス: 引用元論文 306 件、この内訳の 2.6%インド: 引用元論文 288 件、この内訳の 2.4%シンガポール: 引用元論文 272 件、この内訳の 2.3%韓国: 引用元論文 267 件、この内訳の 2.2%
0%23.2%その他 24.5%

機関

分野

  • Computer Science78.6%
  • Engineering9%
  • Medicine2.7%
  • Biochemistry, Genetics and Molecular Biology1.4%
  • Mathematics1.3%
  • Decision Sciences1.3%
  • その他5.7%

トピック

  • Privacy-Preserving Technologies in Data14.2%
  • Stochastic Gradient Optimization Techniques7.3%
  • Topic Modeling3.8%
  • Cryptography and Data Security3.7%
  • Sparse and Compressive Sensing Techniques2.9%
  • Advanced Neural Network Applications2.5%
  • その他65.6%

共著者

全論文

検索で開く
  1. Advances and Open Problems in Federated Learning

    著者: Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao - Foundations and Trends® in Machine Learning, Found. Trends Mach. Learn. 2020 被引用: 4,744

  2. MEDITRON-70B: Scaling Medical Pretraining for Large Language Models

    著者: Zeming Chen, A. Cano, Angelika Romanou, Antoine Bonnet, Kyle Matoba, Francesco Salvi, Matteo Pagliardini, Simin Fan, Andreas Köpf, Amirkeivan Mohtashami, Alexandre Sallinen, Alireza Sakhaeirad, Vinitra Swamy, Igor Krawczuk, Deniz Bayazit, Axel Marmet, Syrielle Montariol, Mary‐Anne Hartley, Martin Jaggi, Antoine Bosselut - arXiv (Cornell University), CoRR 2023 被引用: 428

  3. QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs

    著者: Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, Bo Li, Pashmina Cameron, Martin Jaggi, Dan Alistarh, Torsten Hoefler, James Hensman - Advances in Neural Information Processing Systems 37, NeurIPS 2024 被引用: 582

  4. Advances and Open Problems in Federated Learning

    著者: Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao - CoRR 2019 被引用: 1,103

  5. Ensemble Distillation for Robust Model Fusion in Federated Learning

    著者: Tao Lin, Lingjing Kong, Sebastian U. Stich, Martin Jaggi - NeurIPS 2020 被引用: 1,528

  6. A Field Guide to Federated Optimization

    著者: Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horváth, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu - arXiv (Cornell University), CoRR 2021 被引用: 378

  7. Landmark Attention: Random-Access Infinite Context Length for Transformers

    著者: Amirkeivan Mohtashami, Martin Jaggi - arXiv (Cornell University), CoRR 2023 被引用: 102

  8. FineWeb2: One Pipeline to Scale Them All - Adapting Pre-Training Data Processing to Every Language

    著者: Guilherme Penedo, Hynek Kydlícek, Vinko Sabolcec, Bettina Messmer, Negar Foroutan, Amir Hossein Kargaran, Colin Raffel, Martin Jaggi, Leandro von Werra, Thomas Wolf - ArXiv.org, CoRR 2025 被引用: 76

  9. Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning

    著者: Sai Praneeth Karimireddy, Martin Jaggi, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh - arXiv (Cornell University), CoRR 2020 被引用: 181

  10. Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations

    著者: Alexander Hägele, Elie Bakouch, Atli Kosson, Loubna Ben Allal, Leandro von Werra, Martin Jaggi - Advances in Neural Information Processing Systems 37, NeurIPS 2024 被引用: 146

  11. Unsupervised Learning of Sentence Embeddings Using Compositional n-Gram Features

    著者: Matteo Pagliardini, Prakhar Gupta, Martin Jaggi - Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), NAACL-HLT 2018 被引用: 700

  12. On the Relationship between Self-Attention and Convolutional Layers

    著者: Jean-Baptiste Cordonnier, Andreas Loukas, Martin Jaggi - ICLR 2020 被引用: 647

  13. DOGE: Domain Reweighting with Generalization Estimation

    著者: Simin Fan, Matteo Pagliardini, Martin Jaggi - ICML 2024 被引用: 97

  14. Multi-Head Attention: Collaborate Instead of Concatenate

    著者: Jean-Baptiste Cordonnier, Andreas Loukas, Martin Jaggi - arXiv (Cornell University), CoRR 2020 被引用: 91

  15. Generating Steganographic Text with LSTMs

    著者: Tina Fang, Martin Jaggi, Katerina J. Argyraki - ACL 2017, Student Research Workshop, ACL (Student Research Workshop) 2017 被引用: 141

  16. Benchmarking Optimizers for Large Language Model Pretraining

    著者: Andrei Semenov, Matteo Pagliardini, Martin Jaggi - ArXiv.org, CoRR 2025 被引用: 45

  17. FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings

    著者: Jean Ogier du Terrail, Samy-Safwan Ayed, Edwige Cyffers, Felix Grimberg, Chaoyang He, Regis Loeb, Paul Mangold, Tanguy Marchand, Othmane Marfoq, Erum Mushtaq, Boris Muzellec, Constantin Philippenko, Santiago Silva, Maria Telenczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux - NeurIPS 2022 被引用: 238

  18. Attention with Markov: A Framework for Principled Analysis of Transformers via Markov Chains

    著者: Ashok Vardhan Makkuva, Marco Bondaschi, Adway Girish, Alliot Nagle, Martin Jaggi, Hyeji Kim, Michael Gastpar - arXiv (Cornell University), CoRR 2024 被引用: 41

  19. Learning Aerial Image Segmentation From Online Maps

    著者: Pascal Kaiser, Jan Dirk Wegner, Aurélien Lucchi, Martin Jaggi, Thomas Hofmann, Konrad Schindler - IEEE Transactions on Geoscience and Remote Sensing, IEEE Trans. Geosci. Remote. Sens. 2017 被引用: 278

  20. Byzantine-Robust Decentralized Learning via Self-Centered Clipping

    著者: Lie He, Sai Praneeth Karimireddy, Martin Jaggi - CoRR 2022 被引用: 51

  21. Don't Use Large Mini-Batches, Use Local SGD

    著者: Tao Lin, Sebastian U. Stich, Kumar Kshitij Patel, Martin Jaggi - ICLR 2020 被引用: 470

  22. Masking as an Efficient Alternative to Finetuning for Pretrained Language Models

    著者: Mengjie Zhao, Tao Lin, Fei Mi, Martin Jaggi, Hinrich Schütze - Conference on Empirical Methods in Natural Language Processing (EMNLP), EMNLP (1) 2020 被引用: 75

  23. Byzantine-Robust Learning on Heterogeneous Datasets via Resampling

    著者: Lie He, Sai Praneeth Karimireddy, Martin Jaggi - ICLR 2022 被引用: 200

  24. Distributed Optimization with Arbitrary Local Solvers

    著者: Chenxin Ma, Jakub Konecný, Martin Jaggi, Virginia Smith, Michael I. Jordan, Peter Richtárik, Martin Takác - Optimization methods & software, Optim. Methods Softw. 2017 被引用: 195