Stochastic functional descent for learning Support Vector Machines
暂无分享,去创建一个
[1] Yoav Freund,et al. A decision-theoretic generalization of on-line learning and an application to boosting , 1997, EuroCOLT.
[2] G. Wahba,et al. A Correspondence Between Bayesian Estimation on Stochastic Processes and Smoothing by Splines , 1970 .
[3] J. Friedman. Special Invited Paper-Additive logistic regression: A statistical view of boosting , 2000 .
[4] Quoc V. Le,et al. Proximal regularization for online and batch learning , 2009, ICML '09.
[5] Jason Weston,et al. Fast Kernel Classifiers with Online and Active Learning , 2005, J. Mach. Learn. Res..
[6] J. Platt. Sequential Minimal Optimization : A Fast Algorithm for Training Support Vector Machines , 1998 .
[7] Cordelia Schmid,et al. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[8] Robert Tibshirani,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.
[9] Ohad Shamir,et al. Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization , 2011, ICML.
[10] Yoram Singer,et al. Pegasos: primal estimated sub-gradient solver for SVM , 2011, Math. Program..
[11] Andrew Zisserman,et al. Multiple kernels for object detection , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[12] Yoram Singer,et al. Efficient Online and Batch Learning Using Forward Backward Splitting , 2009, J. Mach. Learn. Res..
[13] Nathan Srebro,et al. The Kernelized Stochastic Batch Perceptron , 2012, ICML.
[14] Thomas Hofmann,et al. Large Margin Methods for Structured and Interdependent Output Variables , 2005, J. Mach. Learn. Res..
[15] Daphne Koller,et al. Multiclass Boosting with Hinge Loss based on Output Coding , 2011, ICML.
[16] Mark W. Schmidt,et al. Block-Coordinate Frank-Wolfe Optimization for Structural SVMs , 2012, ICML.
[17] S. V. N. Vishwanathan,et al. A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning , 2008, J. Mach. Learn. Res..
[18] S. P. Lloyd,et al. Least squares quantization in PCM , 1982, IEEE Trans. Inf. Theory.
[19] Alex Smola,et al. Kernel methods in machine learning , 2007, math/0701907.
[20] Christoph H. Lampert,et al. Learning to Localize Objects with Structured Output Regression , 2008, ECCV.
[21] H. Brendan McMahan,et al. A Unified View of Regularized Dual Averaging and Mirror Descent with Implicit Updates , 2010, 1009.3240.
[22] David A. McAllester,et al. Object Detection with Discriminatively Trained Part Based Models , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[23] Thorsten Joachims,et al. Training structural svms with kernels using sampled cuts , 2008, KDD.
[24] Thorsten Joachims,et al. Cutting-plane training of structural SVMs , 2009, Machine Learning.
[25] G LoweDavid,et al. Distinctive Image Features from Scale-Invariant Keypoints , 2004 .
[26] Ambuj Tewari,et al. Composite objective mirror descent , 2010, COLT 2010.
[27] Lin Xiao,et al. Dual Averaging Methods for Regularized Stochastic Learning and Online Optimization , 2009, J. Mach. Learn. Res..
[28] Koby Crammer,et al. On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines , 2002, J. Mach. Learn. Res..
[29] Stephen P. Boyd,et al. Proximal Algorithms , 2013, Found. Trends Optim..
[30] Stan Sclaroff,et al. Fast globally optimal 2D human detection with loopy graph models , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[31] J. Andrew Bagnell,et al. Maximum margin planning , 2006, ICML.
[32] Charless C. Fowlkes,et al. Discriminative Models for Multi-Class Object Layout , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[33] Pietro Perona,et al. Object class recognition by unsupervised scale-invariant learning , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..
[34] Peter L. Bartlett,et al. Implicit Online Learning , 2010, ICML.
[35] Luc Van Gool,et al. The Pascal Visual Object Classes (VOC) Challenge , 2010, International Journal of Computer Vision.
[36] Alexander J. Smola,et al. Bundle Methods for Machine Learning , 2007, NIPS.
[37] J. Friedman. Greedy function approximation: A gradient boosting machine. , 2001 .