| Metric learning by collapsing classes A Globerson, ST Roweis Advances in neural information processing systems, 451-458, 2006 | 759 | 2006 |
| Fixing max-product: Convergent message passing algorithms for MAP LP-relaxations A Globerson, TS Jaakkola Advances in neural information processing systems, 553-560, 2008 | 364 | 2008 |
| Nightmare at test time: robust learning by feature deletion A Globerson, S Roweis Proceedings of the 23rd international conference on Machine learning, 353-360, 2006 | 337 | 2006 |
| Tightening LP relaxations for MAP using message passing D Sontag, T Meltzer, A Globerson, TS Jaakkola, Y Weiss arXiv preprint arXiv:1206.3288, 2012 | 317 | 2012 |
| Euclidean embedding of co-occurrence data A Globerson, G Chechik, F Pereira, N Tishby Journal of Machine Learning Research 8 (Oct), 2265-2295, 2007 | 255 | 2007 |
| Introduction to dual composition for inference D Sontag, A Globerson, T Jaakkola Optimization for Machine Learning, 2011 | 222 | 2011 |
| Learning Bayesian network structure using LP relaxations T Jaakkola, D Sontag, A Globerson, M Meila Proceedings of the Thirteenth International Conference on Artificial …, 2010 | 219 | 2010 |
| Information bottleneck for Gaussian variables G Chechik, A Globerson, N Tishby, Y Weiss Journal of machine learning research 6 (Jan), 165-188, 2005 | 216 | 2005 |
| Globally optimal gradient descent for a convnet with gaussian inputs A Brutzkus, A Globerson arXiv preprint arXiv:1702.07966, 2017 | 194 | 2017 |
| Exponentiated gradient algorithms for conditional random fields and max-margin markov networks M Collins, A Globerson, T Koo, X Carreras, PL Bartlett Journal of Machine Learning Research 9 (Aug), 1775-1822, 2008 | 189 | 2008 |
| Sgd learns over-parameterized networks that provably generalize on linearly separable data A Brutzkus, A Globerson, E Malach, S Shalev-Shwartz arXiv preprint arXiv:1710.10174, 2017 | 131 | 2017 |
| Sufficient dimensionality reduction A Globerson, N Tishby Journal of Machine Learning Research 3 (Mar), 1307-1331, 2003 | 124 | 2003 |
| Convergent message passing algorithms-a unifying view T Meltzer, A Globerson, Y Weiss arXiv preprint arXiv:1205.2625, 2012 | 122 | 2012 |
| Structured prediction models via the matrix-tree theorem T Koo, A Globerson, X Carreras, M Collins Proceedings of the 2007 Joint Conference on Empirical Methods in Natural …, 2007 | 120 | 2007 |
| Selective sharing for multilingual dependency parsing T Naseem, R Barzilay, A Globerson The Association for Computational Linguistics, 2012 | 119 | 2012 |
| Convex learning with invariances CH Teo, A Globerson, ST Roweis, AJ Smola Advances in neural information processing systems, 1489-1496, 2008 | 112 | 2008 |
| Collective entity resolution with multi-focal attention A Globerson, N Lazic, S Chakrabarti, A Subramanya, M Ringaard, ... | 88 | 2016 |
| Learning efficiently with approximate inference via dual losses O Meshi, D Sontag, T Jaakkola, A Globerson International Machine Learning Society, 2010 | 80 | 2010 |
| An LP View of the M-best MAP problem M Fromer, A Globerson Advances in Neural Information Processing Systems, 567-575, 2009 | 79 | 2009 |
| An alternating direction method for dual MAP LP relaxation O Meshi, A Globerson Joint European conference on machine learning and knowledge discovery in …, 2011 | 70 | 2011 |
Gal ChechikBar Ilan University, NVIDIA確認したメール アドレス: biu.ac.il
