| Petuum: A new platform for distributed machine learning on big data EP Xing, Q Ho, W Dai, JK Kim, J Wei, S Lee, X Zheng, P Xie, A Kumar, ... IEEE transactions on Big Data 1 (2), 49-67, 2015 | 465 | 2015 |
| Semantic pooling for complex event analysis in untrimmed videos X Chang, YL Yu, Y Yang, EP Xing IEEE transactions on pattern analysis and machine intelligence 39 (8), 1617-1632, 2016 | 295 | 2016 |
| Convex multi-view subspace learning M White, Y Yu, X Zhang, D Schuurmans Advances in Neural Information Processing Systems, 1682-1690, 2012 | 144 | 2012 |
| Accelerated training for matrix-norm regularization: A boosting approach X Zhang, Y Yu, D Schuurmans Advances in Neural Information Processing Systems, 2906-2914, 2012 | 110 | 2012 |
| Semantic concept discovery for large-scale zero-shot event detection X Chang, Y Yang, A Hauptmann, EP Xing, YL Yu Twenty-fourth international joint conference on artificial intelligence, 2015 | 99 | 2015 |
| Complex event detection using semantic saliency and nearly-isotonic SVM X Chang, Y Yang, EP Xing, YL Yu ICML, 2015 | 80 | 2015 |
| Analysis of kernel mean matching under covariate shift Y Yu, C Szepesvári ICML, 2012 | 79 | 2012 |
| On Decomposing the Proximal Map. Y Yu NIPS, 91-99, 2013 | 70 | 2013 |
| Better Approximation and Faster Algorithm Using the Proximal Average. Y Yu NIPS, 458-466, 2013 | 64 | 2013 |
| Searching persuasively: Joint event detection and evidence recounting with limited supervision X Chang, YL Yu, Y Yang, AG Hauptmann Proceedings of the 23rd ACM international conference on Multimedia, 581-590, 2015 | 54 | 2015 |
| Sum-of-squares polynomial flow P Jaini, KA Selby, Y Yu International Conference on Machine Learning, 3009-3018, 2019 | 52 | 2019 |
| Deebert: Dynamic early exiting for accelerating bert inference J Xin, R Tang, J Lee, Y Yu, J Lin arXiv preprint arXiv:2004.12993, 2020 | 49 | 2020 |
| Relaxed clipping: A global training method for robust regression and classification Y Yu, M Yang, L Xu, M White, D Schuurmans Advances in neural information processing systems, 2532-2540, 2010 | 44 | 2010 |
| Additive approximations in high dimensional nonparametric regression via the SALSA K Kandasamy, Y Yu International conference on machine learning, 69-78, 2016 | 38 | 2016 |
| Convex sparse coding, subspace learning, and semi-supervised extensions X Zhang, Y Yu, M White, R Huang, D Schuurmans Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011 | 38 | 2011 |
| Generalized conditional gradient for sparse estimation Y Yu, X Zhang, D Schuurmans University of Illinois at Chicago, 2017 | 37 | 2017 |
| Lighter-Communication Distributed Machine Learning via Sufficient Factor Broadcasting. P Xie, JK Kim, Y Zhou, Q Ho, A Kumar, Y Yu, EP Xing UAI, 2016 | 35* | 2016 |
| Rank/norm regularization with closed-form solutions: Application to subspace clustering YL Yu, D Schuurmans arXiv preprint arXiv:1202.3772, 2012 | 35 | 2012 |
| A general projection property for distribution families YL Yu, Y Li, D Schuurmans, C Szepesvári Advances in Neural Information Processing Systems 22, 2232-2240, 2009 | 34 | 2009 |
| They are not equally reliable: Semantic event search using differentiated concept classifiers X Chang, YL Yu, Y Yang, EP Xing Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 31 | 2016 |
Dale SchuurmansResearch Scientist, Google Brain / Professor, University of AlbertaVerified email at cs.ualberta.ca
