| Advances and Open Problems in Federated Learning P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ... arXiv preprint arXiv:1912.04977, 2019 | 5568 | 2019 |
| Revisiting Frank-Wolfe: Projection-Free Sparse Convex Optimization M Jaggi ICML 2013 - Proceedings of the 30th International Conference on Machine Learning, 2013 | 1551 | 2013 |
| Unsupervised learning of sentence embeddings using compositional n-gram features M Pagliardini, P Gupta, M Jaggi NAACL 2018 - Conference of the North American Chapter of the Association for …, 2018 | 879 | 2018 |
| Ensemble Distillation for Robust Model Fusion in Federated Learning T Lin, L Kong, SU Stich, M Jaggi NeurIPS 2020 - Advances in Neural Information Processing Systems, 2020 | 835 | 2020 |
| Sparsified SGD with Memory SU Stich, JB Cordonnier, M Jaggi NeurIPS 2018 - Advances in Neural Information Processing Systems, 2018 | 793 | 2018 |
| On the Relationship between Self-Attention and Convolutional Layers JB Cordonnier, A Loukas, M Jaggi ICLR 2020 - International Conference on Learning Representations, 2020 | 612 | 2020 |
| Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication A Koloskova, SU Stich, M Jaggi ICML 2019 - Proceedings of the 36th International Conference on Machine Learning, 2019 | 507 | 2019 |
| Error Feedback Fixes SignSGD and other Gradient Compression Schemes SP Karimireddy, Q Rebjock, SU Stich, M Jaggi ICML 2019 - Proceedings of the 36th International Conference on Machine Learning, 2019 | 502 | 2019 |
| Don't Use Large Mini-Batches, Use Local SGD T Lin, SU Stich, KK Patel, M Jaggi ICLR 2020 - International Conference on Learning Representations, 2020 | 470 | 2020 |
| On the Global Linear Convergence of Frank-Wolfe Optimization Variants S Lacoste-Julien, M Jaggi NIPS 2015 - Advances in Neural Information Processing Systems, 2015 | 461 | 2015 |
| A Unified Theory of Decentralized SGD with Changing Topology and Local Updates A Koloskova, N Loizou, S Boreiri, M Jaggi, SU Stich ICML 2020 - Proceedings of the 37th International Conference on Machine Learning, 2020 | 456 | 2020 |
| Unsupervised Scalable Representation Learning for Multivariate Time Series JY Franceschi, A Dieuleveut, M Jaggi NeurIPS 2019 - Advances in Neural Information Processing Systems, 2019 | 438 | 2019 |
| Block-Coordinate Frank-Wolfe Optimization for Structural SVMs S Lacoste-Julien, M Jaggi, M Schmidt, P Pletscher ICML 2013 - Proceedings of the 30th International Conference on Machine Learning, 2013 | 427 | 2013 |
| Communication-Efficient Distributed Dual Coordinate Ascent M Jaggi, V Smith, M Takác, J Terhorst, S Krishnan, T Hofmann, MI Jordan NIPS 2014 - Advances in Neural Information Processing Systems, 3068-3076, 2014 | 412 | 2014 |
| Evaluating the Search Phase of Neural Architecture Search K Yu, C Sciuto, M Jaggi, C Musat, M Salzmann ICLR 2020 - International Conference on Learning Representations, 2020 | 391* | 2020 |
| A field guide to federated optimization J Wang, Z Charles, Z Xu, G Joshi, HB McMahan, M Al-Shedivat, G Andrew, ... arXiv preprint arXiv:2107.06917, 2021 | 326 | 2021 |
| Learning Aerial Image Segmentation from Online Maps P Kaiser, JD Wegner, A Lucchi, M Jaggi, T Hofmann, K Schindler IEEE Transactions on Geoscience and Remote Sensing, 2017 | 322 | 2017 |
| CoCoA: A general framework for communication-efficient distributed optimization V Smith, S Forte, C Ma, M Takac, MI Jordan, M Jaggi Journal of Machine Learning Research 18 (230), 1−49, 2018 | 307 | 2018 |
| A Simple Algorithm for Nuclear Norm Regularized Problems M Jaggi, M Sulovsky ICML 2010 - Proceedings of the 27th International Conference on Machine …, 2010 | 301 | 2010 |
| PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization T Vogels, SP Karimireddy, M Jaggi NeurIPS 2019 - Advances in Neural Information Processing Systems, 2019 | 294 | 2019 |
Sebastian Urban StichCISPA Helmholtz Center在 cispa.de 的电子邮件经过验证
