MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks A Gordon, E Eban, O Nachum, B Chen, TJ Yang, E Choi IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 | 396 | 2017 |
A cortical–hippocampal–cortical loop of information processing during memory consolidation G Rothschild, E Eban, LM Frank Nature neuroscience 20 (2), 251-259, 2017 | 386 | 2017 |
Interactive Proofs for Quantum Computations D Aharonov, M Ben-Or, E Eban Innovations in Computer Science (ICS 2008), 2008 | 241* | 2008 |
Scalable Learning of Non-Decomposable Objectives EET Eban, M Schain, A Mackey, A Gordon, RA Saurous, G Elidan Proceedings of the 20th International Conference on Artificial Intelligence …, 2016 | 135 | 2016 |
Seq2Slate: Re-ranking and slate optimization with RNNs I Bello, S Kulkarni, S Jain, C Boutilier, E Chi, E Eban, X Luo, A Mackey, ... arXiv preprint arXiv:1810.02019, 2018 | 84 | 2018 |
Polynomial quantum algorithms for additive approximations of the Potts model and other points of the Tutte plane D Aharonov, I Arad, E Eban, Z Landau Arxiv preprint quant-ph/0702008, 2007 | 76 | 2007 |
Wisdom of committees: An overlooked approach to faster and more accurate models X Wang, D Kondratyuk, E Christiansen, KM Kitani, Y Alon, E Eban arXiv preprint arXiv:2012.01988, 2020 | 72* | 2020 |
Computationally efficient neural image compression N Johnston, E Eban, A Gordon, J Ballé arXiv preprint arXiv:1912.08771, 2019 | 70 | 2019 |
Dynamic Copula Networks for Modeling Real-valued Time Series E Eban, I Nelken, G Rothschild, A Mizrahi, G Elidan Proceedings of the 16th International Conference on Artificial Intelligence …, 2013 | 30 | 2013 |
Learning the Experts for Online Sequence Prediction E Eban, A Birnbaum, S Shalev-Shwartz, A Globerson Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012 | 17 | 2012 |
Structured multi-hashing for model compression E Eban, Y Movshovitz-Attias, H Wu, M Sandler, A Poon, Y Idelbayev, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 16 | 2020 |
Discrete Chebyshev Classifiers E Eban, E Mezuman, A Globerson Proceedings of the 31st International Conference on Machine Learning (ICML …, 2014 | 16 | 2014 |
Sky optimization: Semantically aware image processing of skies in low-light photography O Liba, L Cai, YT Tsai, E Eban, Y Movshovitz-Attias, Y Pritch, H Chen, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 15 | 2020 |
Improper Deep Kernels U Heinemann, R Livni, E Eban, G Elidan, A Globerson The 19th International Conference on Artificial Intelligence and …, 2016 | 15 | 2016 |
FG-SAS: Fine-Grained Stochastic Architecture Search SR Chaudhuri, Y Movshovitz-Attias, E Eban, M Moroz, H Li First ICLR Workshop on Neural Architecture Search (NAS 2020), 2020 | 14* | 2020 |
Differentiable jaccard loss approximation for training an artificial neural network Y Movshovitz-Attias, EET Eban US Patent 10,535,141, 2019 | 12 | 2019 |
Neural network compression Y Alon, E Eban US Patent 11,928,601, 2024 | 11 | 2024 |
Learning neural network structure O Nachum, A Gordon, E Eban, B Chen US Patent 11,315,019, 2022 | 11 | 2022 |
Learning Max-Margin Tree Predictors O Meshi, E Eban, G Elidan, A Globerson Proceedings of the 29th Conference on Uncertainty in Artificial Intelligence …, 2013 | 9 | 2013 |
Constrained classification and ranking via quantiles A Mackey, X Luo, E Eban arXiv preprint arXiv:1803.00067, 2018 | 7 | 2018 |