S. Winawer, R. Fletcher, D. Rex, J. Bond, R. Burt, J. Ferrucci, T. Ganiats, T. Levin, S. Woolf, D. Johnson, L. Kirk, S. Litin, and C. Simmang, "Colorectal cancer screening and surveillance: clinical guidelines and rationale-Update based on new evidence," Gastroenterology, vol. 124, pp. 544-60, Feb 2003.
 K. D. Bodily, J. G. Fletcher, T. Engelby, M. Percival, J. A. Christensen, B. Young, A. J. Krych, D. C. Vander Kooi, D. Rodysill, J. L. Fidler, and C. D. Johnson, "Nonradiologists as second readers for intraluminal findings at CT colonography," Acad Radiol, vol. 12, pp. 67-73, Jan 2005.
 J. G. Fletcher, F. Booya, C. D. Johnson, and D. Ahlquist, "CT colonography: unraveling the twists and turns," Curr Opin Gastroenterol, vol. 21, pp. 90-8, Jan 2005.
 H. Yoshida and A. H. Dachman, "CAD techniques, challenges, and controversies in computed tomographic colonography," Abdom Imaging, vol. 30, pp. 26-41, Jan-Feb 2005.
 H. Yoshida and J. Näppi, "Three-dimensional computer-aided diagnosis scheme for detection of colonic polyps," IEEE Trans Med Imaging, vol. 20, pp. 1261-74, Dec 2001.
 R. M. Summers, C. F. Beaulieu, L. M. Pusanik, J. D. Malley, R. B. Jeffrey, Jr., D. I. Glazer, and S. Napel, "Automated polyp detector for CT colonography: feasibility study," Radiology, vol. 216, pp. 284-90, 2000.
 R. M. Summers, M. Franaszek, M. T. Miller, P. J. Pickhardt, J. R. Choi, and W. R. Schindler, "Computer-aided detection of polyps on oral contrast-enhanced CT colonography," AJR Am J Roentgenol, vol. 184, pp. 105-8, Jan 2005.
 G. Kiss, J. Van Cleynenbreugel, M. Thomeer, P. Suetens, and G. Marchal, "Computer-aided diagnosis in virtual colonography via combination of surface normal and sphere fitting methods," Eur Radiol, vol. 12, pp. 77-81, Jan 2002.
 D. S. Paik, C. F. Beaulieu, G. D. Rubin, B. Acar, R. B. Jeffrey, Jr., J. Yee, J. Dey, and S. Napel, "Surface normal overlap: a computer-aided detection algorithm with application to colonic polyps and lung nodules in helical CT," IEEE Trans Med Imaging, vol. 23, pp. 661-75, Jun 2004.
 A. K. Jerebko, R. M. Summers, J. D. Malley, M. Franaszek, and C. D. Johnson, "Computer-assisted detection of colonic polyps with CT colonography using neural networks and binary classification trees," Med Phys, vol. 30, pp. 52-60, Jan 2003.
 J. Näppi, H. Frimmel, A. H. Dachman, and H. Yoshida, "A new high-performance CAD scheme for the detection of polyps in CT colonography," Medical Imaging 2004: Image Processing, 2004, pp. 839-848.
 A. K. Jerebko, J. D. Malley, M. Franaszek, and R. M. Summers, "Multiple neural network classification scheme for detection of colonic polyps in CT colonography data sets," Acad Radiol, vol. 10, pp. 154-60, Feb 2003.
 A. K. Jerebko, J. D. Malley, M. Franaszek, and R. M. Summers, "Support vector machines committee classification method for computer-aided polyp detection in CT colonography," Acad Radiol, vol. 12, pp. 479-86, Apr 2005.
 V. N. Vapnik, The nature of statistical learning theory, 2nd ed. New York: Springer, 2000.
 R. Courant and D. Hilbert, "Methods of Mathematical Physics," vol. 1, pp. 138-140, 1966.
 O. L. Mangasarian, A.J. Smola, and B. Schölkopf, "Sparse kernel feature analysis," University of Wisconsin, Tech. Rep. 99-04, 1999.
 J. Franc and V. Hlavac, "Statistical Pattern Recognition Toolbox for Matlab," http://cmp.felk.cvut.cz/~xfrancv/stprtool/, 2004.
 [On-line], "Partners Research Computing," http://www.partners.org/rescomputing/, 2006.
 A. J. Smola, B. Schölkopf, "Sparse Greedy Matrix Approximation for Machine Learning", Proc. 17th International Conf. on Machine Learning, 2000.
 X. Jiang, Y. Motai, R. Snapp, and X. Zhu, Accelerated Kernel Feature Analysis, Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 109-116, 2006.
 B. Schölkopf and A. J. Smola, Learning with Kernels, MIT Press, 2002.
 K. Fukunaga and L. Hostetler. Optimization of k-nearest neighbor density estimates. IEEE transactions
on Information Theory, 19(3):320–326, 1973
 J.H. Friedman. Flexible metric nearest neighbor classification. Technical report, Department of
Statistics, Stanford University, Stanford, CA, USA, November 1994.
 T. Hastie and R. Tibshirani. Discriminant adaptive nearest neighbor classification. IEEE Transactions
on Pattern Analysis and Machine Intelligence, 18(6):607–616, 1996.
 D.G. Lowe. Similarity metric learning for a variable-kernel classifier. Neural Computation, 7(1):72–85,
 J. Peng, D.R. Heisterkamp, and H.K. Dai. Adaptive kernel metric nearest neighbor classification. In
Proceedings of the Sixteenth International Conference on Pattern Recognition, volume 3, pages
33–36, Qu´ebec City, Qu´ebec, Canada, 11–15 August 2002.
 Q.B. Gao, Z.Z. Wang, Center-based nearest neighbor classifier, Pattern Recognition 40(2007) 346–349.
 S. Li, J. Lu, Face recognition using the nearest feature line method, IEEE Trans. Neural Networks 10 (2)
 P. Vincent, Y. Bengio, K-local hyperplane and convex distance nearest neighbor algorithms, Advances in
Neural Information Processing Systems (NIPS), vol.14, MIT Press, Cambridge, MA,2002, pp. 985–992.
 W. Zheng, L. Zhao, C. Zou, Locally nearest neighbor classifiers for pattern classification, Pattern
Recognition 37 (2004) 1307–1309.
 Theodoros Damoulas* and Mark A. Girolami, Probabilistic multi-class multi-kernel learning: on protein
fold recognition and remote homology detection, Vol. 24 no. 10 2008, pages 1264–1270,
 S. Amari and S. Wu,”Improving Support Vector Machine Classifiers by Modifying Kernel Functions”,
Neural Networks, Vol.6, pp.783-789, 1999.
 B. Souza and A. de Carvalho,” Gene selection based on multi-class support vector machines and genetic
algorithms”, Molecular Research, Vol 4, NO.3, pp. 599-607, 2005.
 B. Schölkopf and A. J. Smola, Learning with kernels, MIT Press, pp. 211-214, 2002.
 Huilin Xiong, Ya Zhang, and Xue-Wen Chen Data-Dependent Kernel Machines for Microarray Data
Classification. In Proceedings of IEEE/ACM Transactions on Computational Biology and
Binformatics, vol. 4, NO. 4, October-December 2007.
 H. Xiong, M.N.S. Swamy, and M.O. Ahmad, “Optimizing the Data-Dependent Kernel in the Empirical
Feature Space,” IEEE Trans. Neural Networks, vol. 16, pp. 460-474, 2005.
 G.C. Cawley, MATLAB Support Vector Machine Toolbox, School of Information Systems, Univ. of
East Anglia, http://theoval.sys.uea.ac.uk/~gcc/svm/ toolbox, Norwich, U.K., 2000
 Y. Raviv and N. Intrator, “Bootstrapping with Noise: An Efficient Regularization Technique,”
Connection Science, vol. 8, pp. 355-372, 1996.
 Hans Anton Buchholdt “Structural Dynamics For Engineers” Published by Thomas Telford, 1997
 Richard O. Duda, Peter E. Hart, David G. Stork.: Pattern Classification (2nd Edition), John Wiley &
Sons Inc., 2001.
 Bernhard Schökopf , Alexander J. Smola.: Learning with Kernels: Support Vector Machines,
Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning), MIT press,
 H. Fröhlich, O. Chapelle, B. Scholkopf.: Feature selection for support vector machines by means of
genetic algorithm, Tools with Artificial Intelligence, Proceedings. 15th. IEEE International Conference,
pp. 142 – 148, 2003
 Xue-wen Chen.: Gene selection for cancer classification using bootstrapped genetic algorithms and
support vector machines, The Computational Systems, Bioinformatics Conference. Proceedings IEEE
International Conference, pp. 504 – 505, 2003.
 Chanho Park and Sung-Bae Cho.: Genetic search for optimal ensemble of feature-classifier pairs in
DNA gene expression profiles, Neural Networks, 2003. Proceedings of the International Joint
Conference, vol.3, pp. 1702 – 1707, 2003.
 Firooz A. Sadjadi “Polarimetric Radar Target Classification Using Support Vector Machines” Optical
engineering 47(4), 046201 April 2008.
 Tom Briggs, Tim Oates, “Discovering Domain Specific Composite Kernels”.
[†] Y. Motai is with the School of Engineering, Virginia Commonwealth University, Richmond, VA 23284 USA.
[‡] J. Näppi is with the Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114 USA.
[§] H. Yoshida is with the Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114 USA.