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 | 2012 | |
|---|---|---|
| j13 |      | Yiming Ying, Qiang Wu, Colin Campbell: Learning the coordinate gradients. Adv. Comput. Math. 37(3): 355-378 (2012) |
| j12 | | Yiming Ying, Peng Li: Distance Metric Learning with Eigenvalue Optimization. Journal of Machine Learning Research 13: 1-26 (2012) |
| c10 | | |
| i1 | | Qiong Cao, Zheng-Chu Guo, Yiming Ying: Generalization Bounds for Metric and Similarity Learning. CoRR abs/1207.5437 (2012) |
| 2011 | ||
| b1 | | Colin Campbell, Yiming Ying: Learning with Support Vector Machines. Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers 2011 |
| j11 | | Kaizhu Huang, Yiming Ying, Colin Campbell: Generalized sparse metric learning with relative comparisons. Knowl. Inf. Syst. 28(1): 25-45 (2011) |
| 2010 | ||
| j10 | | Yiming Ying, Colin Campbell: Rademacher Chaos Complexities for Learning the Kernel Problem. Neural Computation 22(11): 2858-2886 (2010) |
| 2009 | ||
| j9 | | Yiming Ying, Kaizhu Huang, Colin Campbell: Enhanced protein fold recognition through a novel data integration approach. BMC Bioinformatics 10: 267 (2009) |
| c9 | | |
| c8 | | Peng Li, Yiming Ying, Colin Campbell: A Variational Approach to Semi-Supervised Clustering. ESANN 2009 |
| c7 | | Kaizhu Huang, Yiming Ying, Colin Campbell: GSML: A Unified Framework for Sparse Metric Learning. ICDM 2009: 189-198 |
| c6 | | Yiming Ying, Colin Campbell, Mark Girolami: Analysis of SVM with Indefinite Kernels. NIPS 2009: 2205-2213 |
| c5 | | Yiming Ying, Kaizhu Huang, Colin Campbell: Sparse Metric Learning via Smooth Optimization. NIPS 2009: 2214-2222 |
| c4 | | Yiming Ying, Colin Campbell, Theodoros Damoulas, Mark A. Girolami: Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm. PRIB 2009: 427-438 |
| 2008 | ||
| j8 | | Yiming Ying, Massimiliano Pontil: Online Gradient Descent Learning Algorithms. Foundations of Computational Mathematics 8(5): 561-596 (2008) |
| j7 | | Andrea Caponnetto, Charles A. Micchelli, Massimiliano Pontil, Yiming Ying: Universal Multi-Task Kernels. Journal of Machine Learning Research 9: 1615-1646 (2008) |
| c3 | | Yiming Ying, Colin Campbell: Learning Coordinate Gradients with Multi-Task Kernels. COLT 2008: 217-228 |
| c2 | | Theodoros Damoulas, Yiming Ying, Mark A. Girolami, Colin Campbell: Inferring Sparse Kernel Combinations and Relevance Vectors: An Application to Subcellular Localization of Proteins. ICMLA 2008: 577-582 |
| 2007 | ||
| j6 | | |
| j5 | | Qiang Wu, Yiming Ying, Ding-Xuan Zhou: Multi-kernel regularized classifiers. J. Complexity 23(1): 108-134 (2007) |
| j4 | | Yiming Ying, Ding-Xuan Zhou: Learnability of Gaussians with Flexible Variances. Journal of Machine Learning Research 8: 249-276 (2007) |
| c1 | | Andreas Argyriou, Charles A. Micchelli, Massimiliano Pontil, Yiming Ying: A Spectral Regularization Framework for Multi-Task Structure Learning. NIPS 2007 |
| 2006 | ||
| j3 | | Qiang Wu, Yiming Ying, Ding-Xuan Zhou: Learning Rates of Least-Square Regularized Regression. Foundations of Computational Mathematics 6(2): 171-192 (2006) |
| j2 | | Yiming Ying, Ding-Xuan Zhou: Online Regularized Classification Algorithms. IEEE Transactions on Information Theory 52(11): 4775-4788 (2006) |
| 2004 | ||
| j1 | | Di-Rong Chen, Qiang Wu, Yiming Ying, Ding-Xuan Zhou: Support Vector Machine Soft Margin Classifiers: Error Analysis. Journal of Machine Learning Research 5: 1143-1175 (2004) |
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