Escaping the Curse of Dimensionality in Similarity Learning: Efficient Frank-Wolfe Algorithm and Generalization Bounds
暂无分享,去创建一个
[1] Chih-Jen Lin,et al. Training and Testing Low-degree Polynomial Data Mappings via Linear SVM , 2010, J. Mach. Learn. Res..
[2] Marc Sebban,et al. A Survey on Metric Learning for Feature Vectors and Structured Data , 2013, ArXiv.
[3] Paul Grigas,et al. New analysis and results for the Frank–Wolfe method , 2013, Mathematical Programming.
[4] Philip Wolfe,et al. An algorithm for quadratic programming , 1956 .
[5] Dmitriy Fradkin,et al. Experiments with random projections for machine learning , 2003, KDD '03.
[6] Stephen Tyree,et al. Non-linear Metric Learning , 2012, NIPS.
[7] Alan J. Lee,et al. U-Statistics: Theory and Practice , 1990 .
[8] Shai Ben-David,et al. Understanding Machine Learning: From Theory to Algorithms , 2014 .
[9] Rich Caruana,et al. An empirical evaluation of supervised learning in high dimensions , 2008, ICML '08.
[10] Lijun Zhang,et al. Efficient Stochastic Optimization for Low-Rank Distance Metric Learning , 2017, AAAI.
[11] Martin Jaggi,et al. Sparse Convex Optimization Methods for Machine Learning , 2011 .
[12] Gert R. G. Lanckriet,et al. Robust Structural Metric Learning , 2013, ICML.
[13] R. Freund,et al. New Analysis and Results for the Conditional Gradient Method , 2013 .
[14] Brian Kulis,et al. Metric Learning: A Survey , 2013, Found. Trends Mach. Learn..
[15] Steve R. Gunn,et al. Result Analysis of the NIPS 2003 Feature Selection Challenge , 2004, NIPS.
[16] John F. Canny,et al. Large-scale behavioral targeting , 2009, KDD.
[17] G. Lugosi,et al. Ranking and empirical minimization of U-statistics , 2006, math/0603123.
[18] Rong Jin,et al. Towards Making High Dimensional Distance Metric Learning Practical , 2015, ArXiv.
[19] Inderjit S. Dhillon,et al. Information-theoretic metric learning , 2006, ICML '07.
[20] Samy Bengio,et al. An Online Algorithm for Large Scale Image Similarity Learning , 2009, NIPS.
[21] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[22] Rong Jin,et al. Fine-grained visual categorization via multi-stage metric learning , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[23] Deng Cai,et al. Manifold Adaptive Experimental Design for Text Categorization , 2012, IEEE Transactions on Knowledge and Data Engineering.
[24] Chih-Jen Lin,et al. LIBLINEAR: A Library for Large Linear Classification , 2008, J. Mach. Learn. Res..
[25] R. Serfling. Probability Inequalities for the Sum in Sampling without Replacement , 1974 .
[26] Odalric-Ambrym Maillard,et al. Concentration inequalities for sampling without replacement , 2013, 1309.4029.
[27] Marc Sebban,et al. Similarity Learning for Provably Accurate Sparse Linear Classification , 2012, ICML.
[28] Peng Li,et al. Distance Metric Learning with Eigenvalue Optimization , 2012, J. Mach. Learn. Res..
[29] Martin Jaggi,et al. Revisiting Frank-Wolfe: Projection-Free Sparse Convex Optimization , 2013, ICML.
[30] Stéphan Clémençon,et al. Scaling-up Empirical Risk Minimization: Optimization of Incomplete $U$-statistics , 2015, J. Mach. Learn. Res..
[31] Kristin Branson,et al. Sample Complexity of Learning Mahalanobis Distance Metrics , 2015, NIPS.
[32] Jun Huan,et al. Sparse Compositional Local Metric Learning , 2017, KDD.
[33] Martin Jaggi,et al. On the Global Linear Convergence of Frank-Wolfe Optimization Variants , 2015, NIPS.
[34] W. Hoeffding. A Class of Statistics with Asymptotically Normal Distribution , 1948 .
[35] Amaury Habrard,et al. Robustness and generalization for metric learning , 2012, Neurocomputing.
[36] Tat-Seng Chua,et al. An efficient sparse metric learning in high-dimensional space via l1-penalized log-determinant regularization , 2009, ICML '09.
[37] Qiong Cao,et al. Generalization bounds for metric and similarity learning , 2012, Machine Learning.
[38] Lei Wang,et al. Positive Semidefinite Metric Learning Using Boosting-like Algorithms , 2011, J. Mach. Learn. Res..
[39] Byoung-Tak Zhang,et al. Generative Local Metric Learning for Nearest Neighbor Classification , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[40] Colin McDiarmid,et al. Surveys in Combinatorics, 1989: On the method of bounded differences , 1989 .
[41] Glenn Fung,et al. Learning sparse metrics via linear programming , 2006, KDD '06.
[42] Matthieu Cord,et al. Learning a Distance Metric from Relative Comparisons between Quadruplets of Images , 2016, International Journal of Computer Vision.
[43] Rong Jin,et al. An Integrated Framework for High Dimensional Distance Metric Learning and Its Application to Fine-Grained Visual Categorization , 2014, ArXiv.
[44] Thorsten Joachims,et al. Learning a Distance Metric from Relative Comparisons , 2003, NIPS.
[45] Kenneth L. Clarkson,et al. Coresets, sparse greedy approximation, and the Frank-Wolfe algorithm , 2008, SODA '08.
[46] Cordelia Schmid,et al. Is that you? Metric learning approaches for face identification , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[47] Gao Cong,et al. High-dimensional Similarity Learning via Dual-sparse Random Projection , 2018, IJCAI.
[48] Kilian Q. Weinberger,et al. Distance Metric Learning for Large Margin Nearest Neighbor Classification , 2005, NIPS.
[49] Maik Moeller,et al. An Introduction To Chemoinformatics , 2016 .
[50] Ji Wan,et al. SOML: Sparse Online Metric Learning with Application to Image Retrieval , 2014, AAAI.
[51] Geoffrey E. Hinton,et al. Neighbourhood Components Analysis , 2004, NIPS.
[52] Marc Sebban,et al. Metric Learning , 2015, Metric Learning.
[53] Yuan Shi,et al. Sparse Compositional Metric Learning , 2014, AAAI.
[54] Alexandros Kalousis,et al. Parametric Local Metric Learning for Nearest Neighbor Classification , 2012, NIPS.
[55] Yiming Ying,et al. Guaranteed Classification via Regularized Similarity Learning , 2013, Neural Computation.
[56] Rongrong Ji,et al. Low-Rank Similarity Metric Learning in High Dimensions , 2015, AAAI.
[57] Dacheng Tao,et al. Learning a Distance Metric by Empirical Loss Minimization , 2011, IJCAI.
[58] Patrice Marcotte,et al. Some comments on Wolfe's ‘away step’ , 1986, Math. Program..
[59] Peng Li,et al. Distance Metric Learning Revisited , 2012, ECML/PKDD.
[60] Fei Sha,et al. Similarity Learning for High-Dimensional Sparse Data , 2014, AISTATS.
[61] Rong Jin,et al. Regularized Distance Metric Learning: Theory and Algorithm , 2009, NIPS.
[62] Gal Chechik,et al. Learning Sparse Metrics, One Feature at a Time , 2015, FE@NIPS.
[63] Kaizhu Huang,et al. Sparse Metric Learning via Smooth Optimization , 2009, NIPS.
[64] Holger Rauhut,et al. A Mathematical Introduction to Compressive Sensing , 2013, Applied and Numerical Harmonic Analysis.
[65] Priyanka Agrawal,et al. Link Label Prediction in Signed Social Networks , 2013, IJCAI.
[66] Lalit Jain,et al. Learning Low-Dimensional Metrics , 2017, NIPS.