| Deep canonical correlation analysis G Andrew, R Arora, J Bilmes, K Livescu International conference on machine learning, 1247-1255, 2013 | 1198 | 2013 |
| Scalable training of L1-regularized log-linear models G Andrew, J Gao Proceedings of the 24th international conference on Machine learning, 33-40, 2007 | 625 | 2007 |
| A conditional random field word segmenter for sighan bakeoff 2005 H Tseng, PC Chang, G Andrew, D Jurafsky, CD Manning Proceedings of the fourth SIGHAN workshop on Chinese language Processing, 2005 | 522 | 2005 |
| Tregex and Tsurgeon: tools for querying and manipulating tree data structures. R Levy, G Andrew LREC, 2231-2234, 2006 | 395 | 2006 |
| A portfolio approach to algorithm selection K Leyton-Brown, E Nudelman, G Andrew, J McFadden, Y Shoham IJCAI 3, 1542-1543, 2003 | 187 | 2003 |
| Applied federated learning: Improving google keyboard query suggestions T Yang, G Andrew, H Eichner, H Sun, W Li, N Kong, D Ramage, ... arXiv preprint arXiv:1812.02903, 2018 | 115 | 2018 |
| Query suggestion generation G Andrew, S Park, RL Rounthwaite, S Cucerzan, JP Buckley, J Chan US Patent 7,984,004, 2011 | 104 | 2011 |
| Interactive control of diverse complex characters with neural networks I Mordatch, K Lowrey, G Andrew, Z Popovic, EV Todorov Advances in Neural Information Processing Systems 28, 3132-3140, 2015 | 103 | 2015 |
| A hybrid markov/semi-markov conditional random field for sequence segmentation G Andrew Proceedings of the 2006 Conference on Empirical Methods in Natural Language …, 2006 | 90 | 2006 |
| Boosting as a metaphor for algorithm design K Leyton-Brown, E Nudelman, G Andrew, J McFadden, Y Shoham International Conference on Principles and Practice of Constraint …, 2003 | 83 | 2003 |
| A comparative study of parameter estimation methods for statistical natural language processing J Gao, G Andrew, M Johnson, K Toutanova | 72 | 2007 |
| Weighted linear model R Moore, W Yih, G Andrew, K Toutanova US Patent App. 11/485,015, 2007 | 55 | 2007 |
| Weighted linear model R Moore, W Yih, G Andrew, K Toutanova US Patent App. 11/485,015, 2007 | 55 | 2007 |
| A general approach to adding differential privacy to iterative training procedures HB McMahan, G Andrew, U Erlingsson, S Chien, I Mironov, N Papernot, ... arXiv preprint arXiv:1812.06210, 2018 | 50 | 2018 |
| Differentially private learning with adaptive clipping O Thakkar, G Andrew, HB McMahan arXiv preprint arXiv:1905.03871, 2019 | 43 | 2019 |
| Determining a similarity measure between queries RL Rounthwaite, G Andrew, EM Kiciman, X Yin US Patent 8,606,786, 2013 | 39 | 2013 |
| Sequential deep belief networks G Andrew, J Bilmes 2012 IEEE International Conference on Acoustics, Speech and Signal …, 2012 | 16 | 2012 |
| Verb sense and subcategorization: Using joint inference to improve performance on complementary task G Andrew, T Grenager, CD Manning Proceedings of the 2004 Conference on Empirical Methods in Natural Language …, 2004 | 16 | 2004 |
| TensorFlow privacy G Andrew, S Chien, N Papernot | 15 | 2019 |
| Ranker selection for statistical natural language processing J Gao, G Andrew, M Johnson, K Toutanova US Patent 7,844,555, 2010 | 13 | 2010 |
