| Revisiting Frank-Wolfe: Projection-Free Sparse Convex Optimization M Jaggi ICML 2013 - Proceedings of the 30th International Conference on Machine Learning, 2013 | 1003 | 2013 |
| 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 | 677 | 2019 |
| 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 | 457 | 2018 |
| 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 | 367 | 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 | 325 | 2014 |
| On the Global Linear Convergence of Frank-Wolfe Optimization Variants S Lacoste-Julien, M Jaggi NIPS 2015 - Advances in Neural Information Processing Systems, 2015 | 305 | 2015 |
| A Simple Algorithm for Nuclear Norm Regularized Problems M Jaggi, M Sulovsky ICML 2010 - Proceedings of the 27th International Conference on Machine …, 2010 | 269 | 2010 |
| Sparsified SGD with Memory SU Stich, JB Cordonnier, M Jaggi NeurIPS 2018 - Advances in Neural Information Processing Systems, 2018 | 242 | 2018 |
| 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 | 172 | 2017 |
| Don't Use Large Mini-Batches, Use Local SGD T Lin, SU Stich, KK Patel, M Jaggi ICLR 2020 - International Conference on Learning Representations, 2019 | 171 | 2019 |
| Adding vs. averaging in distributed primal-dual optimization C Ma, V Smith, M Jaggi, MI Jordan, P Richtárik, M Takáč ICML 2015 - Proceedings of the 32th International Conference on Machine …, 2015 | 170 | 2015 |
| 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 | 165 | 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 | 160 | 2019 |
| 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 | 156 | 2018 |
| 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, 2019 | 153* | 2019 |
| SwissCheese at SemEval-2016 Task 4: Sentiment Classification Using an Ensemble of Convolutional Neural Networks with Distant Supervision J Deriu, M Gonzenbach, F Uzdilli, A Lucchi, V De Luca, M Jaggi SemEval-2016 - Proceedings of the 10th International Workshop on Semantic …, 2016 | 117 | 2016 |
| Leveraging Large Amounts of Weakly Supervised Data for Multi-Language Sentiment Classification J Deriu, A Lucchi, V De Luca, A Severyn, S Müller, M Cieliebak, ... WWW 2017 - International World Wide Web Conference, 2017 | 108 | 2017 |
| Distributed Optimization with Arbitrary Local Solvers C Ma, J Konečný, M Jaggi, V Smith, MI Jordan, P Richtárik, M Takáč Optimization Methods and Software 32 (4), 813-848, 2017 | 104 | 2017 |
| Sparse Convex Optimization Methods for Machine Learning M Jaggi ETH Zürich, 2011 | 101 | 2011 |
| On the Relationship between Self-Attention and Convolutional Layers JB Cordonnier, A Loukas, M Jaggi ICLR 2020 - International Conference on Learning Representations, 2019 | 85 | 2019 |
Sebastian Urban StichResearch Scientist, EPFLVerified email at epfl.ch
