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Top 100 SVM Publications
JOACHIMS, T., 1997. Text Categorization with Support Vector Machines: Learning with Many Relevant Features . Springer. [Cited by 2277 ] (216.02/year)
CRISTIANINI, N. and J. SHAWE-TAYLOR, 2000. An introduction to Support Vector Machines . [Cited by 1509 ] (200.11/year)
CORTES, C. and V. VAPNIK, 1995. Support-vector networks . Machine Learning. [Cited by 2683 ] (213.94/year)
BURGES, C.J.C., 1998. A Tutorial on Support Vector Machines for Pattern Recognition . Data Mining and Knowledge Discovery. [Cited by 3793 ] (397.56/year)
SCHOLKOPF, B. and A.J. SMOLA, 2001. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. MIT Press Cambridge, MA, USA. [Cited by 1824 ] (278.87/year)
JOACHIMS, T., 1999. 11 Making Large-Scale Support Vector Machine Learning Practical . Advances in Kernel Methods: Support Vector Learning. [Cited by 1522 ] (178.20/year)
BROWN, M.P.S., et al. , 2000. Knowledge-based analysis of microarray gene expression data by using support vector machines . Proceedings of the National Academy of Sciences. [Cited by 1134 ] (150.38/year)
CHANG, C.C. and C.J. LIN, 2001. LIBSVM: a library for support vector machines . Software available at http://www. csie. ntu. edu. tw/cjlin/ …. [Cited by 1623 ] (248.14/year)
PLATT, J.C., 1999. 12 Fast Training of Support Vector Machines Using Sequential Minimal Optimization . Advances in Kernel Methods: Support Vector Learning. [Cited by 1442 ] (168.84/year)
OSUNA, E., R. FREUND and F. GIROSI…, 1997. Training support vector machines: an application to face detection . Proceedings of the IEEE Conference on Computer Vision and …. [Cited by 1104 ] (104.74/year)
CRISTIANINI, N. and J. SHAWE-TAYLOR, 2000. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods . books.google.com. [Cited by 2354 ] (312.17/year)
FUREY, T.S., et al. , 2000. Support vector machine classification and validation of cancer tissue samples using microarray … . Bioinformatics. [Cited by 703 ] (93.23/year)
SUYKENS, J.A.K. and J. VANDEWALLE, 1999. Least Squares Support Vector Machine Classifiers . Neural Processing Letters. [Cited by 613 ] (71.77/year)
HSU, C.W. and C.J. LIN, 2002. A comparison of methods for multiclass support vector machines . Neural Networks, IEEE Transactions on. [Cited by 858 ] (154.85/year)
OSUNA, E., R. FREUND and F. GIROSI, An improved training algorithm for support vector machines . ieeexplore.ieee.org. [Cited by 512 ] (?/year)
JOACHIMS, T., 1999. Making large-scale support vector machine learning practical . Advances in kernel methods: support vector learning table of …. [Cited by 423 ] (49.53/year)
JOACHIMS, T., 1999. Transductive inference for text classification using support vector machines . Proceedings of the Sixteenth International Conference on …. [Cited by 580 ] (67.91/year)
SMOLA, A.J. and B. SCHöLKOPF, 2004. A tutorial on support vector regression . Statistics and Computing. [Cited by 811 ] (229.05/year)
GUYON, I., et al. , 2002. Gene Selection for Cancer Classification using Support Vector Machines . Machine Learning. [Cited by 793 ] (143.12/year)
PLATT, J., 1999. Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods . Advances in Large Margin Classifiers. [Cited by 559 ] (65.45/year)
VAPNIK, V., S.E. GOLOWICH and A. SMOLA, 1997. Support Vector Method for Function Approximation, Regression Estimation, and Signal Processing . Advances in Neural Information Processing Systems 9. [Cited by 448 ] (42.50/year)
WESTON, J. and C. WATKINS, 1999. Multi-class support vector machines . Proceedings ESANN, Brussels. [Cited by 380 ] (44.49/year)
PLATT, J., 1999. Sequential minimal optimization: A fast algorithm for training support vector machines . Advances in Kernel Methods-Support Vector Learning. [Cited by 464 ] (54.33/year)
GUNN, S.R., 1998. Support Vector Machines for Classification and Regression . ISIS Technical Report. [Cited by 518 ] (54.29/year)
SCHöLKOPF, B., C.J.C. BURGES and A.J. SMOLA, 1999. Advances in Kernel Methods: Support Vector Learning . books.google.com. [Cited by 173 ] (20.26/year)
SCHöLKOPF, B. and A.J. SMOLA, 2002. Learning With Kernels: Support Vector Machines, Regularization, Optimization, and Beyond . books.google.com. [Cited by 786 ] (141.86/year)
CHAPELLE, O., et al. , 2002. Choosing Multiple Parameters for Support Vector Machines . Machine Learning. [Cited by 453 ] (81.76/year)
SCHOLKOPF, B., et al. , 2000. New Support Vector Algorithms . Neural Computation. [Cited by 452 ] (59.94/year)
SUYKENS, J.A.K., 2002. Least Squares Support Vector Machines . books.google.com. [Cited by 519 ] (93.67/year)
SCHOLKOPF, B., et al. , 1997. Comparing support vector machines with Gaussian kernels to radialbasis function classifiers . Signal Processing, IEEE Transactions on [see also Acoustics, …. [Cited by 385 ] (36.52/year)
SCHöLKOPF, B., 1997. Support Vector Learning. R. Oldenbourg Verlag. [Cited by 333 ] (31.59/year)
SCHOLKOPF, B., C.J.C. BURGES and A.J. SMOLA…, 1999. Advances in Kernel Methods: Support Vector Learning. [Cited by 435 ] (50.93/year)
DRUCKER, H., D. WU and V.N. VAPNIK, 1999. Support Vector Machines for Spam Categorization . IEEE TRANSACTIONS ON NEURAL NETWORKS. [Cited by 331 ] (38.76/year)
COLLOBERT, R. and S. BENGIO, 2001. SVMTorch: Support Vector Machines for Large-Scale Regression Problems . Journal of Machine Learning Research. [Cited by 355 ] (54.27/year)
EVGENIOU, T., M. PONTIL and T. POGGIO, 2000. 10 Regularization Networks and Support Vector Machines . Advances in Large-Margin Classifiers. [Cited by 417 ] (55.30/year)
HUA, S. and Z. SUN, 2001. Support vector machine approach for protein subcellular localization prediction . Bioinformatics. [Cited by 329 ] (50.30/year)
TONG, S. and E. CHANG, 2001. Support vector machine active learning for image retrieval . Proceedings of the ninth ACM international conference on …. [Cited by 353 ] (53.97/year)
PONTIL, M. and A. VERRI, 1998. Support vector machines for 3 D object recognition . IEEE Transactions on Pattern Analysis and Machine …. [Cited by 327 ] (34.27/year)
JOACHIMS, T., 2002. Learning to Classify Text Using Support Vector Machines . books.google.com. [Cited by 460 ] (83.02/year)
CHAPELLE, O., P. HAFFNER and V.N. VAPNIK, 1999. Support vector machines for histogram-based image classification . Neural Networks, IEEE Transactions on. [Cited by 323 ] (37.82/year)
OSUNA, E., R. FREUND and F. GIROSI, 1997. Support Vector Machines: Training and Applications . [Cited by 330 ] (31.31/year)
MULLER, K.R., et al. , 1997. Predicting time series with support vector machines . Proceedings of the International Conference on Artificial …. [Cited by 242 ] (22.96/year)
BURGES, C.J.C. and B. SCHOLKOPF, 1997. Improving the Accuracy and Speed of Support Vector Machines . Advances in Neural Information Processing Systems 9. [Cited by 221 ] (20.97/year)
DRUCKER, H., et al. , 1997. Support Vector Regression Machines . Advances in Neural Information Processing Systems 9. [Cited by 228 ] (21.63/year)
CAUWENBERGHS, G., et al. , 2001. Incremental and Decremental Support Vector Machine Learning . Advances in Neural Information Processing Systems 13. [Cited by 200 ] (30.58/year)
BEN-HUR, A., et al. , 2001. Support vector clustering . Journal of Machine Learning Research. [Cited by 272 ] (41.59/year)
TONG, S. and D. KOLLER, 2002. Support vector machine active learning with applications to text classification . The Journal of Machine Learning Research. [Cited by 329 ] (59.38/year)
BURGES, C.J.C., 1996. Simplified support vector decision rules . Proceedings of the 13th International Conference on Machine …. [Cited by 249 ] (21.58/year)
GIROSI, F., 1998. An Equivalence Between Sparse Approximation And Support Vector Machines . Neural Computation. [Cited by 308 ] (32.28/year)
SYED, N., H. LIU and K.K. SUNG, 1999. Incremental learning with support vector machines . … of the Workshop on Support Vector Machines at the …. [Cited by 127 ] (14.87/year)
BRADLEY, P.S. and O.L. MANGASARIAN, 1998. Feature selection via concave minimization and support vector machines . Machine Learning Proceedings of the Fifteenth International …. [Cited by 212 ] (22.22/year)
WESTON, J. and C. WATKINS, 1999. Support vector machines for multi-class pattern recognition . Proceedings of the Seventh European Symposium On Artificial …. [Cited by 170 ] (19.90/year)
HSU, C.W., C.C. CHANG and C.J. LIN…, 2003. A practical guide to support vector classification . National Taiwan University, Tech. Rep., July. [Cited by 258 ] (56.82/year)
BENNETT, K. and A. DEMIRIZ, 1998. Semi-supervised support vector machines . Advances in Neural Information Processing Systems. [Cited by 181 ] (18.97/year)
KUDO, T. and Y. MATSUMOTO, 2001. Chunking with support vector machines . North American Chapter Of The Association For Computational …. [Cited by 233 ] (35.62/year)
DING, C.H.Q. and I. DUBCHAK, 2001. Multi-class protein fold recognition using support vector machines and neural networks . Bioinformatics. [Cited by 265 ] (40.52/year)
CORTES, C. and V. VAPNIK, 1995. Support-vector network. Machine Learning. [Cited by 312 ] (24.88/year)
ZIEN, A., et al. , 2000. Engineering support vector machine kernels that recognize translation initiation sites . Bioinformatics. [Cited by 235 ] (31.16/year)
WAHBA, G., 1999. 6 Support Vector Machines, Reproducing Kernel Hubert Spaces, and Randomized GACV . Advances in Kernel Methods: Support Vector Learning. [Cited by 212 ] (24.82/year)
SMOLA, A.J., B. SCHöLKOPF and K.R. MüLLER, 1998. The connection between regularization operators and support vector kernels . Neural Networks. [Cited by 222 ] (23.27/year)
AMARI, S. and S. WU, 1999. Improving support vector machine classifiers by modifying kernel functions . Neural Networks. [Cited by 170 ] (19.90/year)
TAX, D.M.J. and R.P.W. DUIN, 1999. Support vector domain description . Pattern Recognition Letters. [Cited by 201 ] (23.53/year)
HEARST, M.A., et al. , 1998. Support vector machines . IEEE Intelligent Systems. [Cited by 212 ] (22.22/year)
HUA, S. and Z. SUN, 2001. … method of protein secondary structure prediction with high segment overlap measure: support vector … . Journal of Molecular Biology. [Cited by 213 ] (32.56/year)
LEE, Y.J. and O.L. MANGASARIAN, 2001. RSVM: Reduced support vector machines . Proceedings of the First SIAM International Conference on …. [Cited by 199 ] (30.42/year)
FRIE, T.T., N. CRISTIANINI and C. CAMPBELL, Proc. ICML. The kernel adatron algorithm: A fast and simple learning procedure for support vector machines.," . [Cited by 171 ] (?/year)
SCHOLKOPF, B., C. BURGES and V. VAPNIK, 1996. Incorporating invariances in support vector learning machines . Artificial Neural Networks| ICANN. [Cited by 127 ] (11.00/year)
SCHOHN, G. and D. COHN, 2000. Less is more: Active learning with support vector machines . Proceedings of the Seventeenth International Conference on …. [Cited by 160 ] (21.22/year)
PLATT, J.C., 1999. … support vector machines using sequential minimal optimization, Advances in kernel methods: support …. [Cited by 181 ] (21.19/year)
KREβEL…, U., 1999. Pairwise classification and support vector machines. Advances in Kernel Methods: Support Vector Learning. [Cited by 171 ] (20.02/year)
MANGASARIAN, O.L. and D.R. MUSICANT, 1999. Successive overrelaxation for support vector machines . Neural Networks, IEEE Transactions on. [Cited by 164 ] (19.20/year)
CHAPELLE, O. and V. VAPNIK, 1999. Model selection for support vector machines . Advances in Neural Information Processing Systems. [Cited by 135 ] (15.81/year)
JI, K., et al. , 2002. Tuning support vector machines for biomedical named entity recognition . Association for Computation Linguistics Workshop on Natural …. [Cited by 111 ] (20.03/year)
KUDOH, T. and Y. MATSUMOTO, 2000. Use of support vector learning for chunk identification . Proceedings of the 2nd workshop on Learning language in …. [Cited by 122 ] (16.18/year)
FUNG, G.M. and O.L. MANGASARIAN, 2005. Multicategory Proximal Support Vector Machine Classifiers . Machine Learning. [Cited by 178 ] (70.06/year)
SUYKENS, J.A.K., et al. , 2002. Weighted least squares support vector machines: robustness and sparse approximation . Neurocomputing. [Cited by 164 ] (29.60/year)
SCHOLKOPF, B., et al. , 1998. Prior knowledge in support vector kernels . Advances in Neural Information Processing Systems. [Cited by 149 ] (15.62/year)
MANGASARIAN, O.L., 2000. 8 Generalized Support Vector Machines . Advances in Large-Margin Classifiers. [Cited by 139 ] (18.43/year)
MANGASARIAN, O.L. and D.R. MUSICANT, 2001. Lagrangian Support Vector Machines . Journal of Machine Learning Research. [Cited by 164 ] (25.07/year)
BURBIDGE, R., et al. , 2001. Drug design by machine learning: support vector machines for pharmaceutical data analysis . Computers and Chemistry. [Cited by 166 ] (25.38/year)
MUKHERJEE, S., et al. , 1999. Support vector machine classification of microarray data . CBCL Paper. [Cited by 107 ] (12.53/year)
KEERTHI, S.S., et al. , 2000. A fast iterative nearest point algorithm for support vector machineclassifier design . Neural Networks, IEEE Transactions on. [Cited by 166 ] (22.01/year)
KEERTHI, S.S. and C.J. LIN, 2003. Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel . Neural Computation. [Cited by 180 ] (39.64/year)
HEISELE, B., P. HO and T. POGGIO, Proc. 8th International Conference on Computer Vision. Face recognition with support vector machines: Global versus component-based approach . [Cited by 146 ] (?/year)
GUO, G., S.Z. LI and K. CHAN, 2001. Face recognition by support vector machines . Image and Vision Computing. [Cited by 133 ] (20.33/year)
TSOCHANTARIDIS, I., et al. , 2004. Support vector machine learning for interdependent and structured output spaces . ACM International Conference Proceeding Series. [Cited by 158 ] (44.62/year)
CRISTIANINI, N. and J. SHAWE-TAYLOR, 2000. Support Vector Machines . [Cited by 128 ] (16.97/year)
VAPNIK, V. and O. CHAPELLE, 2000. Bounds on Error Expectation for Support Vector Machines . Neural Computation. [Cited by 131 ] (17.37/year)
BARTLETT, P. and J. SHAWE-TAYLOR, 1999. Generalization Performance of Support Vector Machines and Other Pattern Classifiers . Advances in Kernel Methods: Support Vector Learning. [Cited by 126 ] (14.75/year)
SCHOLKOPF, B. and A.J. SMOLA, 2002. Learning with Kernels: Support Vector Machines, Regularization. Optimization, and Beyond. MIT Press. [Cited by 185 ] (33.39/year)
SCHOLKOPF, B., C. BURGES and V. VAPNIK, 1995. Extracting Support Data for a Given Task . Knowledge Discovery and Data Mining. [Cited by 298 ] (23.76/year)
DECOSTE, D. and B. SCHöLKOPF, 2002. Training Invariant Support Vector Machines . Machine Learning. [Cited by 159 ] (28.70/year)
ALTUN, Y., I. TSOCHANTARIDIS and T. HOFMANN, 2003. Hidden markov support vector machines . Proc. ICML. [Cited by 136 ] (29.95/year)
WAHBA, G., Y. LIN and H. ZHANG, 2000. Generalized approximate cross validation for support vector machines . Advances in Large Margin Classifiers. [Cited by 65 ] (8.62/year)
PHILLIPS, P.J., 1999. Support vector machines applied to face recognition - all 4 versions » . MIT Press Cambridge, MA, USA. [Cited by 121 ] (14.17/year)
LEE, Y.J. and O.L. MANGASARIAN, 2001. SSVM: A Smooth Support Vector Machine for Classification . Computational Optimization and Applications. [Cited by 133 ] (20.33/year)
KARCHIN, R., K. KARPLUS and D. HAUSSLER, 2002. Classifying G-protein coupled receptors with support vector machines . Bioinformatics. [Cited by 146 ] (26.35/year)
CHANG, C.C. and C.J. LIN, 2001. Training ?-Support Vector Classifiers: Theory and Algorithms . Neural Computation. [Cited by 133 ] (20.33/year)
SUYKENS, J.A.K., L. LUKAS and J. VANDEWALLE, 2000. Sparse approximation using least squares support vector machines . Circuits and Systems, 2000. Proceedings. ISCAS 2000 Geneva. …. [Cited by 82 ] (10.87/year)
LIN, C.F. and S.D. WANG, 2002. Fuzzy support vector machines . IEEE Transactions on Neural Networks. [Cited by 118 ] (21.30/year)