Wei Chen (陈薇)
Wei Chen (陈薇)
Microsoft Research
Verified email at microsoft.com - Homepage
Title
Cited by
Cited by
Year
Lightgbm: A highly efficient gradient boosting decision tree
G Ke, Q Meng, T Finley, T Wang, W Chen, W Ma, Q Ye, TY Liu
Advances in neural information processing systems, 3146-3154, 2017
22222017
A theoretical analysis of NDCG ranking measures
Y Wang, L Wang, Y Li, D He, W Chen, TY Liu
Proceedings of the 26th annual conference on learning theory (COLT 2013) 8, 6, 2013
1792013
Ranking measures and loss functions in learning to rank
W Chen, TY Liu, Y Lan, ZM Ma, H Li
Advances in Neural Information Processing Systems, 315-323, 2009
1592009
Asynchronous stochastic gradient descent with delay compensation
S Zheng, Q Meng, T Wang, W Chen, N Yu, ZM Ma, TY Liu
International Conference on Machine Learning, 4120-4129, 2017
1102017
On the depth of deep neural networks: A theoretical view
S Sun, W Chen, L Wang, X Liu, TY Liu
arXiv preprint arXiv:1506.05232, 2015
882015
Dual supervised learning
Y Xia, T Qin, W Chen, J Bian, N Yu, TY Liu
arXiv preprint arXiv:1707.00415, 2017
832017
A communication-efficient parallel algorithm for decision tree
Q Meng, G Ke, T Wang, W Chen, Q Ye, ZM Ma, TY Liu
Advances in Neural Information Processing Systems, 1279-1287, 2016
592016
A game-theoretic machine learning approach for revenue maximization in sponsored search
D He, W Chen, L Wang, TY Liu
Twenty-Third International Joint Conference on Artificial Intelligence, 2013
472013
Efficient inexact proximal gradient algorithm for nonconvex problems
Q Yao, JT Kwok, F Gao, W Chen, TY Liu
arXiv preprint arXiv:1612.09069, 2016
412016
Sponsored search auctions: Recent advances and future directions
T Qin, W Chen, TY Liu
ACM Transactions on Intelligent Systems and Technology (TIST) 5 (4), 1-34, 2015
392015
Towards binary-valued gates for robust lstm training
Z Li, D He, F Tian, W Chen, T Qin, L Wang, TY Liu
arXiv preprint arXiv:1806.02988, 2018
342018
Asynchronous stochastic gradient descent with delay compensation for distributed deep learning
S Zheng, Q Meng, T Wang, W Chen, N Yu, Z Ma, TY Liu
arXiv preprint arXiv:1609.08326, 2016
342016
Convergence analysis of distributed stochastic gradient descent with shuffling
Q Meng, W Chen, Y Wang, ZM Ma, TY Liu
Neurocomputing 337, 46-57, 2019
312019
Finite sample analysis of the GTD policy evaluation algorithms in Markov setting
Y Wang, W Chen, Y Liu, ZM Ma, TY Liu
Advances in Neural Information Processing Systems, 5504-5513, 2017
252017
Ensemble-compression: A new method for parallel training of deep neural networks
S Sun, W Chen, J Bian, X Liu, TY Liu
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017
202017
Asynchronous stochastic proximal optimization algorithms with variance reduction
Q Meng, W Chen, J Yu, T Wang, ZM Ma, TY Liu
Thirty-First AAAI Conference on Artificial Intelligence, 2017
182017
Asynchronous Accelerated Stochastic Gradient Descent.
Q Meng, W Chen, J Yu, T Wang, Z Ma, TY Liu
IJCAI, 1853-1859, 2016
172016
-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space
Q Meng, S Zheng, H Zhang, W Chen, ZM Ma, TY Liu
arXiv preprint arXiv:1802.03713, 2018
142018
Large margin deep neural networks: Theory and algorithms
S Sun, W Chen, L Wang, TY Liu
arXiv preprint arXiv:1506.05232 148, 2015
142015
Training over-parameterized deep resnet is almost as easy as training a two-layer network
H Zhang, D Yu, W Chen, TY Liu
arXiv preprint arXiv:1903.07120, 2019
132019
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