| Streaming submodular maximization: Massive data summarization on the fly A Badanidiyuru, B Mirzasoleiman, A Karbasi, A Krause ACM SIGKDD international conference on Knowledge discovery and data mining …, 2014 | 353 | 2014 |
| Lazier Than Lazy Greedy B Mirzasoleiman, A Badanidiyuru, A Karbasi, J Vondrák, A Krause AAAI Conference on Artificial Intelligence (AAAI), 1812-1818, 2015 | 347 | 2015 |
| Distributed submodular maximization: Identifying representative elements in massive data B Mirzasoleiman, A Karbasi, R Sarkar, A Krause Advances in Neural Information Processing Systems (NIPS), 2049-2057, 2013 | 272 | 2013 |
| Cascaded failures in weighted networks B Mirzasoleiman, M Babaei, M Jalili, MA Safari Physical Review E 84 (4), 046114, 2011 | 184 | 2011 |
| Fast constrained submodular maximization: Personalized data summarization B Mirzasoleiman, A Badanidiyuru, A Karbasi International Conference on Machine Learning (ICML), 1358-1367, 2016 | 139 | 2016 |
| Guaranteed non-convex optimization: Submodular maximization over continuous domains Y Bian, B Mirzasoleiman, JM Buhmann, A Krause International conference on Artificial Intelligence and Statistics (AISTATS), 2016 | 137 | 2016 |
| Coresets for Data-efficient Training of Machine Learning Models B Mirzasoleiman, J Bilmes, J Leskovec International Conference on Machine Learning (ICML), 2020 | 134 | 2020 |
| Selection via proxy: Efficient data selection for deep learning C Coleman, C Yeh, S Mussmann, B Mirzasoleiman, P Bailis, P Liang, ... International Conference on Learning Representations (ICLR), 2020 | 133 | 2020 |
| Distributed submodular maximization B Mirzasoleiman, A Karbasi, R Sarkar, A Krause Journal of Machine Learning Research 17 (238), 1−44, 2016 | 80 | 2016 |
| Streaming Non-monotone Submodular Maximization: Personalized Video Summarization on the Fly B Mirzasoleiman, S Jegelka, A Krause AAAI Conference on Artificial Intelligence (AAAI), 2018 | 74 | 2018 |
| Coresets for robust training of deep neural networks against noisy labels B Mirzasoleiman, K Cao, J Leskovec Advances in Neural Information Processing Systems 33, 11465-11477, 2020 | 67 | 2020 |
| Deletion-Robust Submodular Maximization: Data Summarization with “the Right to be Forgotten” B Mirzasoleiman, A Karbasi, A Krause International Conference on Machine Learning (ICML), 2449-2458, 2017 | 67 | 2017 |
| Fast distributed submodular cover: Public-private data summarization B Mirzasoleiman, M Zadimoghaddam, A Karbasi Advances in Neural Information Processing Systems (NIPS), 3594-3602, 2016 | 57 | 2016 |
| Distributed submodular cover: Succinctly summarizing massive data B Mirzasoleiman, A Karbasi, A Badanidiyuru, A Krause Advances in Neural Information Processing Systems (NIPS), 2881-2889, 2015 | 52 | 2015 |
| On the fairness of time-critical influence maximization in social networks J Ali, M Babaei, A Chakraborty, B Mirzasoleiman, KP Gummadi, A Singla Transactions on Knowledge and Data Engineering (TKDE), 1541-1542, 2021 | 32 | 2021 |
| Learning sparse combinatorial representations via two-stage submodular maximization E Balkanski, B Mirzasoleiman, A Krause, Y Singer International Conference on Machine Learning (ICML), 2207-2216, 2016 | 28 | 2016 |
| Revenue maximization in social networks through discounting M Babaei, B Mirzasoleiman, M Jalili, MA Safari Social Network Analysis and Mining 3, 1249-1262, 2013 | 27 | 2013 |
| Immunizing complex networks with limited budget B Mirzasoleiman, M Babaei, M Jalili Europhysics Letters 98 (3), 38004, 2012 | 19 | 2012 |
| CrossWalk: Fairness-enhanced Node Representation Learning A Khajehnejad, M Khajehnejad, M Babaei, KP Gummadi, A Weller, ... AAAI Conference on Artificial Intelligence (AAAI), 2021 | 17 | 2021 |
| Dynamic Network Model from Partial Observations E Ghalebi, B Mirzasoleiman, R Grosu, J Leskovec Advances in Neural Information Processing Systems, 9883-9893, 2018 | 15 | 2018 |
Andreas KrauseProfessor of Computer Science, ETH ZurichVerified email at inf.ethz.ch
