Minmin Chen
Minmin Chen
Research scientist, Google
Verified email at - Homepage
Cited by
Cited by
Marginalized denoising auto-encoders for nonlinear representations
M Chen, K Weinberger, F Sha, Y Bengio
International conference on machine learning, 1476-1484, 2014
Co-training for domain adaptation
M Chen, KQ Weinberger, J Blitzer
Advances in neural information processing systems 24, 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
Fast image tagging
M Chen, A Zheng, K Weinberger
International conference on machine learning, 1274-1282, 2013
AntisymmetricRNN: A dynamical system view on recurrent neural networks
B Chang, M Chen, E Haber, EH Chi
arXiv preprint arXiv:1902.09689, 2019
Learning with marginalized corrupted features
L Maaten, M Chen, S Tyree, K Weinberger
International Conference on Machine Learning, 410-418, 2013
Efficient vector representation for documents through corruption
M Chen
arXiv preprint arXiv:1707.02377, 2017
Cost-sensitive tree of classifiers
Z Xu, M Kusner, K Weinberger, M Chen
International conference on machine learning, 133-141, 2013
Automatic Feature Decomposition for Single View Co-training.
M Chen, KQ Weinberger, Y Chen
ICML 2 (3), 5, 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
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
Classifier cascade for minimizing feature evaluation cost
M Chen, Z Xu, K Weinberger, O Chapelle, D Kedem
Artificial Intelligence and Statistics, 218-226, 2012
F. Sha. Marginalized denoising autoencoders for domain adaptation
M Chen, Z Xu, K Weinberger
Proceedings of the 29th International Conference on Machine Learning, 767-774, 2012
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
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
An alternative text representation to tf-idf and bag-of-words
M Chen, KQ Weinberger, F Sha
arXiv preprint arXiv:1301.6770, 2013
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
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
Surrogate for long-term user experience in recommender systems
Y Wang, M Sharma, C Xu, S Badam, Q Sun, L Richardson, L Chung, ...
Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and …, 2022
Values of user exploration in recommender systems
M Chen, Y Wang, C Xu, Y Le, M Sharma, L Richardson, SL Wu, E Chi
Proceedings of the 15th ACM Conference on Recommender Systems, 85-95, 2021
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