Metric Learning: A Survey
暂无分享,去创建一个
[1] Nello Cristianini,et al. Kernel Methods for Pattern Analysis , 2003, ICTAI.
[2] L. Bregman. The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming , 1967 .
[3] Thomas Gärtner,et al. A survey of kernels for structured data , 2003, SKDD.
[4] Kilian Q. Weinberger,et al. Large Margin Multi-Task Metric Learning , 2010, NIPS.
[5] Hal Daumé,et al. Frustratingly Easy Domain Adaptation , 2007, ACL.
[6] Cordelia Schmid,et al. Is that you? Metric learning approaches for face identification , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[7] Donald E. Porter,et al. Improved error reporting for software that uses black-box components , 2007, PLDI '07.
[8] Nello Cristianini,et al. Kernel Methods for Pattern Analysis: References , 2004 .
[9] Trevor Darrell,et al. Adapting Visual Category Models to New Domains , 2010, ECCV.
[10] Gene H. Golub,et al. Matrix computations , 1983 .
[11] Kilian Q. Weinberger,et al. Distance Metric Learning for Large Margin Nearest Neighbor Classification , 2005, NIPS.
[12] Inderjit S. Dhillon,et al. Inductive Regularized Learning of Kernel Functions , 2010, NIPS.
[13] C. Stein,et al. Estimation with Quadratic Loss , 1992 .
[14] Thorsten Joachims,et al. Learning a Distance Metric from Relative Comparisons , 2003, NIPS.
[15] Kilian Q. Weinberger,et al. ISMIR 2008 – Session 3a – Content-Based Retrieval, Categorization and Similarity 1 LEARNING A METRIC FOR MUSIC SIMILARITY , 2022 .
[16] Jon Louis Bentley,et al. An Algorithm for Finding Best Matches in Logarithmic Expected Time , 1977, TOMS.
[17] Kaizhu Huang,et al. Sparse Metric Learning via Smooth Optimization , 2009, NIPS.
[18] Martin Zinkevich,et al. Online Convex Programming and Generalized Infinitesimal Gradient Ascent , 2003, ICML.
[19] Roger Fletcher,et al. A New Variational Result for Quasi-Newton Formulae , 1991, SIAM J. Optim..
[20] Andrew Zisserman,et al. A Statistical Approach to Material Classification Using Image Patch Exemplars , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[21] Boris Polyak,et al. Constrained minimization methods , 1966 .
[22] Guy Lebanon,et al. Metric learning for text documents , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[23] Stephen P. Boyd,et al. Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.
[24] Geoffrey E. Hinton,et al. Neighbourhood Components Analysis , 2004, NIPS.
[25] Piotr Indyk,et al. Approximate nearest neighbors: towards removing the curse of dimensionality , 1998, STOC '98.
[26] Pierre Priouret,et al. Adaptive Algorithms and Stochastic Approximations , 1990, Applications of Mathematics.
[27] Yoram Singer,et al. Online and batch learning of pseudo-metrics , 2004, ICML.
[28] Kilian Q. Weinberger,et al. Metric Learning for Kernel Regression , 2007, AISTATS.
[29] Piotr Indyk,et al. Approximate Nearest Neighbor: Towards Removing the Curse of Dimensionality , 2012, Theory Comput..
[30] Pavel Zezula,et al. M-tree: An Efficient Access Method for Similarity Search in Metric Spaces , 1997, VLDB.
[31] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[32] Lorenzo Torresani,et al. Large Margin Component Analysis , 2006, NIPS.
[33] Jeffrey K. Uhlmann,et al. Satisfying General Proximity/Similarity Queries with Metric Trees , 1991, Inf. Process. Lett..
[34] Kilian Q. Weinberger,et al. Fast solvers and efficient implementations for distance metric learning , 2008, ICML '08.
[35] Rong Jin,et al. Regularized Distance Metric Learning: Theory and Algorithm , 2009, NIPS.
[36] Raymond J. Mooney,et al. Integrating constraints and metric learning in semi-supervised clustering , 2004, ICML.
[37] Trevor Darrell,et al. The Pyramid Match Kernel: Efficient Learning with Sets of Features , 2007, J. Mach. Learn. Res..
[38] Stephen Tyree,et al. Non-linear Metric Learning , 2012, NIPS.
[39] Jitendra Malik,et al. Learning Globally-Consistent Local Distance Functions for Shape-Based Image Retrieval and Classification , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[40] Prateek Jain,et al. Fast image search for learned metrics , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[41] Gang Hua,et al. Discriminant Embedding for Local Image Descriptors , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[42] Samy Bengio,et al. An Online Algorithm for Large Scale Image Similarity Learning , 2009, NIPS.
[43] Huilin Xiong,et al. Kernel-based distance metric learning for microarray data classification , 2006, BMC Bioinformatics.
[44] Dimitri P. Bertsekas,et al. Nonlinear Programming , 1997 .
[45] Koby Crammer,et al. Online Passive-Aggressive Algorithms , 2003, J. Mach. Learn. Res..
[46] Gert R. G. Lanckriet,et al. Metric Learning to Rank , 2010, ICML.
[47] Steven M. Seitz,et al. Photo tourism: exploring photo collections in 3D , 2006, ACM Trans. Graph..
[48] A. Goldstein. Convex programming in Hilbert space , 1964 .
[49] P. Mahalanobis. On the generalized distance in statistics , 1936 .
[50] Radford M. Neal. Pattern Recognition and Machine Learning , 2007, Technometrics.
[51] Samuel Kaski,et al. Informative Discriminant Analysis , 2003, ICML.
[52] Inderjit S. Dhillon,et al. Information-theoretic metric learning , 2006, ICML '07.
[53] Prateek Jain,et al. Fast Similarity Search for Learned Metrics , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[54] Qiong Cao,et al. Generalization bounds for metric and similarity learning , 2012, Machine Learning.
[55] Du Tran,et al. Human Activity Recognition with Metric Learning , 2008, ECCV.
[56] Inderjit S. Dhillon,et al. Learning low-rank kernel matrices , 2006, ICML.
[57] Kristin J. Dana,et al. 3D Texture Recognition Using Bidirectional Feature Histograms , 2004, International Journal of Computer Vision.
[58] Nello Cristianini,et al. Classification using String Kernels , 2000 .
[59] R. Dykstra,et al. A Method for Finding Projections onto the Intersection of Convex Sets in Hilbert Spaces , 1986 .
[60] Inderjit S. Dhillon,et al. Structured metric learning for high dimensional problems , 2008, KDD.
[61] G. McLachlan. Discriminant Analysis and Statistical Pattern Recognition , 1992 .
[62] Inderjit S. Dhillon,et al. Metric and Kernel Learning Using a Linear Transformation , 2009, J. Mach. Learn. Res..
[63] Alexander J. Smola,et al. Learning with kernels , 1998 .
[64] Wei Liu,et al. Learning Distance Metrics with Contextual Constraints for Image Retrieval , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[65] Sam T. Roweis,et al. EM Algorithms for PCA and SPCA , 1997, NIPS.
[66] Amir Globerson,et al. Metric Learning by Collapsing Classes , 2005, NIPS.
[67] Matthew E. Taylor,et al. Metric learning for reinforcement learning agents , 2011, AAMAS.
[68] Yann LeCun,et al. Learning a similarity metric discriminatively, with application to face verification , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[69] Trevor Darrell,et al. Fast pose estimation with parameter-sensitive hashing , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[70] Gábor Lugosi,et al. Prediction, learning, and games , 2006 .
[71] Masao Nakagawa,et al. Metric learning for DNA microarray data analysis , 2009 .
[72] Michael I. Jordan,et al. Distance Metric Learning with Application to Clustering with Side-Information , 2002, NIPS.
[73] Inderjit S. Dhillon,et al. Low-Rank Kernel Learning with Bregman Matrix Divergences , 2009, J. Mach. Learn. Res..
[74] Marc Teboulle,et al. Mirror descent and nonlinear projected subgradient methods for convex optimization , 2003, Oper. Res. Lett..
[75] Michael E. Tipping,et al. Probabilistic Principal Component Analysis , 1999 .
[76] Bernhard Schölkopf,et al. Learning with kernels , 2001 .
[77] Peng Li,et al. Distance Metric Learning with Eigenvalue Optimization , 2012, J. Mach. Learn. Res..
[78] Inderjit S. Dhillon,et al. Online Metric Learning and Fast Similarity Search , 2008, NIPS.
[79] Trevor Darrell,et al. What you saw is not what you get: Domain adaptation using asymmetric kernel transforms , 2011, CVPR 2011.
[80] Ivor W. Tsang,et al. Learning with Idealized Kernels , 2003, ICML.
[81] Boonserm Kijsirikul,et al. A new kernelization framework for Mahalanobis distance learning algorithms , 2010, Neurocomputing.
[82] Bernhard Schölkopf,et al. Nonlinear Component Analysis as a Kernel Eigenvalue Problem , 1998, Neural Computation.
[83] Geoffrey E. Hinton,et al. Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure , 2007, AISTATS.