| Marginalized denoising autoencoders for domain adaptation M Chen, Z Xu, K Weinberger, F Sha arXiv preprint arXiv:1206.4683, 2012 | 995 | 2012 |
| Co-training for domain adaptation M Chen, KQ Weinberger, J Blitzer Advances in neural information processing systems 24, 2011 | 503 | 2011 |
| Top-k off-policy correction for a REINFORCE recommender system M Chen, A Beutel, P Covington, S Jain, F Belletti, EH Chi Proceedings of the Twelfth ACM International Conference on Web Search and …, 2019 | 415 | 2019 |
| Fast image tagging M Chen, A Zheng, K Weinberger International conference on machine learning, 1274-1282, 2013 | 269 | 2013 |
| AntisymmetricRNN: A dynamical system view on recurrent neural networks B Chang, M Chen, E Haber, EH Chi arXiv preprint arXiv:1902.09689, 2019 | 203 | 2019 |
| Learning with marginalized corrupted features L Maaten, M Chen, S Tyree, K Weinberger International Conference on Machine Learning, 410-418, 2013 | 202 | 2013 |
| Marginalized denoising auto-encoders for nonlinear representations M Chen, K Weinberger, F Sha, Y Bengio International conference on machine learning, 1476-1484, 2014 | 168 | 2014 |
| Efficient vector representation for documents through corruption M Chen arXiv preprint arXiv:1707.02377, 2017 | 155 | 2017 |
| Cost-sensitive tree of classifiers Z Xu, M Kusner, K Weinberger, M Chen International conference on machine learning, 133-141, 2013 | 142 | 2013 |
| Automatic Feature Decomposition for Single View Co-training. M Chen, KQ Weinberger, Y Chen ICML 2 (3), 5, 2011 | 121 | 2011 |
| Dynamical isometry and a mean field theory of RNNs: Gating enables signal propagation in recurrent neural networks M Chen, J Pennington, S Schoenholz International Conference on Machine Learning, 873-882, 2018 | 111 | 2018 |
| Classifier cascades and trees for minimizing feature evaluation cost Z Xu, MJ Kusner, KQ Weinberger, M Chen, O Chapelle The Journal of Machine Learning Research 15 (1), 2113-2144, 2014 | 106 | 2014 |
| Classifier cascade for minimizing feature evaluation cost M Chen, Z Xu, K Weinberger, O Chapelle, D Kedem Artificial Intelligence and Statistics, 218-226, 2012 | 99* | 2012 |
| Towards neural mixture recommender for long range dependent user sequences J Tang, F Belletti, S Jain, M Chen, A Beutel, C Xu, E H. Chi The World Wide Web Conference, 1782-1793, 2019 | 81 | 2019 |
| Off-policy learning in two-stage recommender systems J Ma, Z Zhao, X Yi, J Yang, M Chen, J Tang, L Hong, EH Chi Proceedings of The Web Conference 2020, 463-473, 2020 | 78 | 2020 |
| Toward a two-tier clinical warning system for hospitalized patients G Hackmann, M Chen, O Chipara, C Lu, Y Chen, M Kollef, TC Bailey AMIA Annual Symposium Proceedings 2011, 511, 2011 | 45 | 2011 |
| An alternative text representation to tf-idf and bag-of-words M Chen, KQ Weinberger, F Sha arXiv preprint arXiv:1301.6770, 2013 | 44* | 2013 |
| Minimalrnn: Toward more interpretable and trainable recurrent neural networks M Chen arXiv preprint arXiv:1711.06788, 2017 | 34 | 2017 |
| User response models to improve a reinforce recommender system M Chen, B Chang, C Xu, EH Chi Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021 | 32 | 2021 |
| Dynamical isometry and a mean field theory of LSTMs and GRUs D Gilboa, B Chang, M Chen, G Yang, SS Schoenholz, EH Chi, ... arXiv preprint arXiv:1901.08987, 2019 | 32 | 2019 |
Zhixiang (Eddie) XuWashington UniversityVerified email at cse.wustl.edu
