| Lazier Than Lazy Greedy B Mirzasoleiman, A Badanidiyuru, A Karbasi, J Vondrák, A Krause arXiv preprint arXiv:1409.7938, 2015 | 382 | 2015 |
| Streaming submodular maximization: Massive data summarization on the fly A Badanidiyuru, B Mirzasoleiman, A Karbasi, A Krause Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 371 | 2014 |
| Distributed submodular maximization: Identifying representative elements in massive data B Mirzasoleiman, A Karbasi, R Sarkar, A Krause Advances in Neural Information Processing Systems 26, 2013 | 295 | 2013 |
| There is no single functional atlas even for a single individual: Functional parcel definitions change with task M Salehi, AS Greene, A Karbasi, X Shen, D Scheinost, RT Constable NeuroImage 208, 116366, 2020 | 163 | 2020 |
| Fast constrained submodular maximization: Personalized data summarization B Mirzasoleiman, A Badanidiyuru, A Karbasi International Conference on Machine Learning, 1358-1367, 2016 | 157 | 2016 |
| Graph-constrained group testing M Cheraghchi, A Karbasi, S Mohajer, V Saligrama IEEE Transactions on Information Theory 58 (1), 248-262, 2012 | 156 | 2012 |
| Graph-constrained group testing M Cheraghchi, A Karbasi, S Mohajer, V Saligrama Information Theory Proceedings (ISIT), 2010 IEEE International Symposium on …, 2010 | 156 | 2010 |
| Learning local error bars for nonlinear regression D Nix, A Weigend Advances in neural information processing systems 7, 1994 | 148* | 1994 |
| Near-optimally teaching the crowd to classify A Singla, I Bogunovic, G Bartók, A Karbasi, A Krause International Conference on Machine Learning, 154-162, 2014 | 147 | 2014 |
| Gradient methods for submodular maximization H Hassani, M Soltanolkotabi, A Karbasi Advances in Neural Information Processing Systems 30, 2017 | 125 | 2017 |
| Stochastic conditional gradient methods: From convex minimization to submodular maximization A Mokhtari, H Hassani, A Karbasi The Journal of Machine Learning Research 21 (1), 4232-4280, 2020 | 112 | 2020 |
| Streaming weak submodularity: Interpreting neural networks on the fly E Elenberg, AG Dimakis, M Feldman, A Karbasi Advances in Neural Information Processing Systems 30, 2017 | 103 | 2017 |
| Submodular streaming in all its glory: Tight approximation, minimum memory and low adaptive complexity E Kazemi, M Mitrovic, M Zadimoghaddam, S Lattanzi, A Karbasi International Conference on Machine Learning, 3311-3320, 2019 | 97 | 2019 |
| Submodular maximization beyond non-negativity: Guarantees, fast algorithms, and applications C Harshaw, M Feldman, J Ward, A Karbasi International Conference on Machine Learning, 2634-2643, 2019 | 90 | 2019 |
| Greed is good: Near-optimal submodular maximization via greedy optimization M Feldman, C Harshaw, A Karbasi Conference on Learning Theory, 758-784, 2017 | 90 | 2017 |
| Distributed submodular maximization B Mirzasoleiman, A Karbasi, R Sarkar, A Krause The Journal of Machine Learning Research 17 (1), 8330-8373, 2016 | 86 | 2016 |
| Online continuous submodular maximization L Chen, H Hassani, A Karbasi International Conference on Artificial Intelligence and Statistics, 1896-1905, 2018 | 82 | 2018 |
| Do less, get more: Streaming submodular maximization with subsampling M Feldman, A Karbasi, E Kazemi Advances in Neural Information Processing Systems 31, 2018 | 79 | 2018 |
| Scalable deletion-robust submodular maximization: Data summarization with privacy and fairness constraints E Kazemi, M Zadimoghaddam, A Karbasi International conference on machine learning, 2544-2553, 2018 | 77* | 2018 |
| Deletion-robust submodular maximization: Data summarization with “the right to be forgotten” B Mirzasoleiman, A Karbasi, A Krause International Conference on Machine Learning, 2449-2458, 2017 | 77 | 2017 |
Andreas KrauseProfessor of Computer Science, ETH ZurichVerified email at inf.ethz.ch
