Accelerating stochastic gradient descent using predictive variance reduction R Johnson, T Zhang Advances in neural information processing systems 26, 2013 | 3012 | 2013 |
A framework for learning predictive structures from multiple tasks and unlabeled data. RK Ando, T Zhang Journal of Machine Learning Research 6 (11), 2005 | 1689 | 2005 |
Solving large scale linear prediction problems using stochastic gradient descent algorithms T Zhang Proceedings of the twenty-first international conference on Machine learning …, 2004 | 1448 | 2004 |
Text mining: predictive methods for analyzing unstructured information SM Weiss, N Indurkhya, T Zhang, F Damerau Springer Science & Business Media, 2010 | 1195 | 2010 |
Stochastic dual coordinate ascent methods for regularized loss minimization. S Shalev-Shwartz, T Zhang Journal of Machine Learning Research 14 (1), 2013 | 1181 | 2013 |
Effective use of word order for text categorization with convolutional neural networks R Johnson, T Zhang arXiv preprint arXiv:1412.1058, 2014 | 1095 | 2014 |
Statistical behavior and consistency of classification methods based on convex risk minimization T Zhang The Annals of Statistics 32 (1), 56-85, 2004 | 960 | 2004 |
Nonlinear learning using local coordinate coding K Yu, T Zhang, Y Gong Advances in neural information processing systems 22, 2009 | 950 | 2009 |
Efficient mini-batch training for stochastic optimization M Li, T Zhang, Y Chen, AJ Smola Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 931 | 2014 |
A proximal stochastic gradient method with progressive variance reduction L Xiao, T Zhang SIAM Journal on Optimization 24 (4), 2057-2075, 2014 | 812 | 2014 |
Deep pyramid convolutional neural networks for text categorization R Johnson, T Zhang Proceedings of the 55th Annual Meeting of the Association for Computational …, 2017 | 778 | 2017 |
The epoch-greedy algorithm for multi-armed bandits with side information J Langford, T Zhang Advances in neural information processing systems 20, 2007 | 699 | 2007 |
Image classification using super-vector coding of local image descriptors X Zhou, K Yu, T Zhang, TS Huang Computer Vision–ECCV 2010: 11th European Conference on Computer Vision …, 2010 | 693 | 2010 |
Learning with structured sparsity J Huang, T Zhang, D Metaxas Proceedings of the 26th Annual International Conference on Machine Learning …, 2009 | 650 | 2009 |
Named entity recognition through classifier combination R Florian, A Ittycheriah, H Jing, T Zhang Proceedings of the seventh conference on Natural language learning at HLT …, 2003 | 645 | 2003 |
The benefit of group sparsity J Huang, T Zhang | 611 | 2010 |
Stochastic gradient descent for non-smooth optimization: Convergence results and optimal averaging schemes O Shamir, T Zhang International conference on machine learning, 71-79, 2013 | 608 | 2013 |
Analysis of multi-stage convex relaxation for sparse regularization. T Zhang Journal of Machine Learning Research 11 (3), 2010 | 595 | 2010 |
A spectral algorithm for learning hidden Markov models D Hsu, SM Kakade, T Zhang Journal of Computer and System Sciences 78 (5), 1460-1480, 2012 | 592 | 2012 |
Communication-efficient distributed optimization using an approximate newton-type method O Shamir, N Srebro, T Zhang International conference on machine learning, 1000-1008, 2014 | 585 | 2014 |