Towards good practice in large-scale learning for image classification
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Cordelia Schmid | Zeynep Akata | Florent Perronnin | Zaid Harchaoui | F. Perronnin | C. Schmid | Z. Harchaoui | Zeynep Akata
[1] Jason Weston,et al. Multi-Class Support Vector Machines , 1998 .
[2] Koby Crammer,et al. On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines , 2002, J. Mach. Learn. Res..
[3] Thorsten Joachims,et al. Optimizing search engines using clickthrough data , 2002, KDD.
[4] David G. Lowe,et al. Distinctive Image Features from Scale-Invariant Keypoints , 2004, International Journal of Computer Vision.
[5] Ryan M. Rifkin,et al. In Defense of One-Vs-All Classification , 2004, J. Mach. Learn. Res..
[6] Ambuj Tewari,et al. On the Consistency of Multiclass Classification Methods , 2007, J. Mach. Learn. Res..
[7] Thomas Hofmann,et al. Large Margin Methods for Structured and Interdependent Output Variables , 2005, J. Mach. Learn. Res..
[8] Eric Horvitz,et al. Considering Cost Asymmetry in Learning Classifiers , 2006, J. Mach. Learn. Res..
[9] Michael I. Jordan,et al. Convexity, Classification, and Risk Bounds , 2006 .
[10] Thorsten Joachims,et al. Training linear SVMs in linear time , 2006, KDD '06.
[11] Filip Radlinski,et al. A support vector method for optimizing average precision , 2007, SIGIR.
[12] Jason Weston,et al. Solving multiclass support vector machines with LaRank , 2007, ICML '07.
[13] Florent Perronnin,et al. Fisher Kernels on Visual Vocabularies for Image Categorization , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[14] Léon Bottou,et al. The Tradeoffs of Large Scale Learning , 2007, NIPS.
[15] Yoram Singer,et al. Pegasos: primal estimated sub-gradient solver for SVM , 2007, ICML '07.
[16] Tie-Yan Liu,et al. Directly optimizing evaluation measures in learning to rank , 2008, SIGIR.
[17] Chih-Jen Lin,et al. LIBLINEAR: A Library for Large Linear Classification , 2008, J. Mach. Learn. Res..
[18] Antonio Torralba,et al. Ieee Transactions on Pattern Analysis and Machine Intelligence 1 80 Million Tiny Images: a Large Dataset for Non-parametric Object and Scene Recognition , 2022 .
[19] Cordelia Schmid,et al. Constructing Category Hierarchies for Visual Recognition , 2008, ECCV.
[20] Subhransu Maji,et al. Max-margin additive classifiers for detection , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[21] Yanjun Qi,et al. Supervised semantic indexing , 2009, ECIR.
[22] Li Fei-Fei,et al. ImageNet: A large-scale hierarchical image database , 2009, CVPR.
[23] Patrick Gallinari,et al. Ranking with ordered weighted pairwise classification , 2009, ICML '09.
[24] Yihong Gong,et al. Locality-constrained Linear Coding for image classification , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[25] Thomas Mensink,et al. Improving the Fisher Kernel for Large-Scale Image Classification , 2010, ECCV.
[26] Florent Perronnin,et al. Large-scale image categorization with explicit data embedding , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[27] Thomas S. Huang,et al. Image Classification Using Super-Vector Coding of Local Image Descriptors , 2010, ECCV.
[28] Andrew Zisserman,et al. Efficient additive kernels via explicit feature maps , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[29] Fei-Fei Li,et al. What Does Classifying More Than 10, 000 Image Categories Tell Us? , 2010, ECCV.
[30] Jason Weston,et al. Label Embedding Trees for Large Multi-Class Tasks , 2010, NIPS.
[31] Jason Weston,et al. Large scale image annotation: learning to rank with joint word-image embeddings , 2010, Machine Learning.
[32] Andrew W. Fitzgibbon,et al. Efficient Object Category Recognition Using Classemes , 2010, ECCV.
[33] Cordelia Schmid,et al. Product Quantization for Nearest Neighbor Search , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[34] Ming Yang,et al. Large-scale image classification: Fast feature extraction and SVM training , 2011, CVPR 2011.
[35] Andrew Zisserman,et al. The devil is in the details: an evaluation of recent feature encoding methods , 2011, BMVC.
[36] Sebastian Nowozin,et al. Structured Learning and Prediction in Computer Vision , 2011, Found. Trends Comput. Graph. Vis..
[37] Daphne Koller,et al. Discriminative learning of relaxed hierarchy for large-scale visual recognition , 2011, 2011 International Conference on Computer Vision.
[38] Bernt Schiele,et al. Evaluating knowledge transfer and zero-shot learning in a large-scale setting , 2011, CVPR 2011.
[39] Florent Perronnin,et al. High-dimensional signature compression for large-scale image classification , 2011, CVPR 2011.
[40] Klaus-Robert Müller,et al. Efficient BackProp , 2012, Neural Networks: Tricks of the Trade.