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Report (52)

Report
Chen, Y.; Fu, Q.; Gu, L.; Li, S.; Schölkopf, B.; Zhang, H.: Kernel Machine Based Learning for Multi-View Face Detection and Pose Estimation. Microsoft Research, Microsoft Corporation, Redmond, VA, USA (2001)
Report
Gretton, A.; Herbrich R, Schölkopf, B.; Rayner, P.: Bound on the Leave-One-Out Error for 2-Class Classification using nu-SVMs. (2001)
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Gretton, A.; Herbrich R, Schölkopf, B.; Smola, A.; Rayner, P.: Bound on the Leave-One-Out Error for Density Support Estimation using nu-SVMs. (2001)
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Weston, J.; Elisseeff, A.; Schölkopf, B.: Use of the $ell_0$-norm with linear models and kernel methods. Biowulf Technologies, Savannah, GA, USA (2001)
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Schölkopf, B.; Platt, J.; Shawe-Taylor, J.; Smola, A.; Williamson, R.: Estimating the support of a high-dimensional distribution. Microsoft Research, Microsoft Corporation, Redmond, VA, USA (2000), 30 pp.
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Schölkopf, B.: The Kernel Trick for Distances. Microsoft Research, Microsoft Corporation, Redmond, WA, USA (2000), 9 pp.
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Schölkopf, B.; Platt, J.; Smola, A.: Kernel method for percentile feature extraction. Microsoft Research, Microsoft Corporation, Redmond, WA, USA (2000)
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Smola, A.; Mangasarian, O.; Schölkopf, B.: Sparse Kernel Feature Analysis. University of Wisconsin, Data Mining Institute, Madison, WI, USA (1999), 21 pp.
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Schölkopf, B.; Shawe-Taylor, J.; Smola, A.; Williamson, R.: Generalization Bounds via Eigenvalues of the Gram matrix. University of London: Royal Holloway College: NeuroCOLT 2, London, UK (1999), 15 pp.
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Smola, A.; Mika, S.; Schölkopf, B.: Quantization Functionals and Regularized Principal Manifolds. University of London, Royal Holloway College, NeuroCOLT 2, London, UK (1998), 9 pp.
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Smola, A.; Williamson, R.; Schölkopf, B.: Generalization bounds and learning rates for Regularized principal manifolds. University of London, Royal Holloway College, NeuroCOLT 2, London, UK (1998), 9 pp.
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Smola, A.; Williamson, R.; Schölkopf, B.: Generalization Bounds for Convex Combinations of Kernel Functions. University of London, Royal Holloway College, NeuroCOLT 2, London, UK (1998), 11 pp.
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Williamson, R.; Smola, A.; Schölkopf, B.: Generalization Performance of Regularization Networks and Support Vector Machines via Entropy Numbers of Compact Operators. University of London, Royal Holloway College, NeuroCOLT 2, London, UK (1998), 39 pp.
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Saunders, C.; Stitson, M.; Weston, J.; Bottou, L.; Schölkopf, B.; Smola, A.: Support Vector Machine Reference Manual. Department of Computer Science, Royal Holloway, University of London, London, UK (1998), 26 pp.
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Franz, M.; Schölkopf, B.; Bülthoff, H.: Homing by parameterized scene matching (Technical Report of the Max Planck Institute for Biological Cybernetics, 46). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (1997)
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Schölkopf, B.; Smola, A.; Müller, K.-R.: Nonlinear Component Analysis as a Kernel Eigenvalue Problem (Technical Report of the Max Planck Institute for Biological Cybernetics, 44). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (1996)
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Franz, M.; Schölkopf, B.; Georg, P.; Mallot, H.; Bülthoff, H.: Learning View Graphs for Robot Navigation (Technical Report of the Max Planck Institute for Biological Cybernetics, 33). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (1996)
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Vapnik, V.; Burges, C.; Schölkopf, B.: A New Method for Constructing Artificial Neural Networks. AT & T, Bell Laboratories, Murray Hill, NJ, USA (1995)
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Schölkopf, B.; Mallot, H.: View-based cognitive mapping and path planning (Technical Report of the Max Planck Institute for Biological Cybernetics, 7). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (1994), 30 pp.

Other (2)

Other
Hofmann, M.; Schölkopf, B.; Steinke, F.; Pichler, B.: MR/PET Attenuation Correction, (2006)
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