PUBLICATIONS

Papers

  1. Caponnetto A., Bertero M.
    Tomography with a Finite Set of Projections: Singular Value Decomposition and Resolution.
    Inverse Problems, Volume: 13, pp.: 815-833, (1997).

  2. Bindi D., Caponnetto A.
    Tomographic Imaging of the Earthquake Source: Numerical Validation in Two-Dimensional Approximation.
    Journal of Geophysical Research - Solid Earth, Volume: 106, N B4, p.643, (2001).

  3. Bindi D., Caponnetto A.
    Analysis of the Compatibility Conditions for the Radon Projections, with an Application to Seismology.
    Int. J. Imaging Syst. Technol., Volume: 12, pp.: 112-116, (2002).

  4. Rosasco L., De Vito E., Caponnetto A., Piana M., Verri A.
    Are Loss Functions All the Same? [pdf]
    Neural Computation, Volume: 16, pp.: 1063-1076, (2004).

  5. De Vito E., Rosasco L., Caponnetto A., Piana M., Verri A.
    Some Properties of Regularized Kernel Methods. [pdf]
    Journal of Machine Learning Research 5 (2004) 1363-1390.

  6. Rosasco L., Caponnetto A., De Vito E., De Giovannini U., Odone F.
    Learning, Regularization and Ill-Posed Inverse Problems. [pdf]
    Conference proceedings: Eighteenth Annual Conference on Neural Information Processing Systems, 2004.

  7. Caponnetto A., Rosasco L., Odone F., Verri A.
    Support Vectors Algorithms as Regularization Networks. [pdf]
    Conference proceedings: 13th European Symposium on Artificial Neural Networks, April 2005.

  8. De Vito E., Caponnetto A., Rosasco L.
    Model Selection for Regularized Least-Squares Algorithm in Learning Theory. [pdf]
    Foundations of Computational Mathematics, 5(1) 59-85, February 2005.

  9. De Vito E., Rosasco L., Caponnetto A., De Giovannini U., Odone F.
    Learning from Examples as an Inverse Problem. [pdf]
    Journal of Machine Learning Research 6(May) 883-904, 2005.

  10. Rakhlin A., Caponnetto A.
    Stability of K-Means Clustering.
    Conference proceedings: Twentieth Annual Conference on Neural Information Processing Systems, 2006.

  11. De Vito E., Caponnetto A., Rosasco L.
    Discretization Error Analysis for Tikhonov Regularization in Learning Theory.
    Analysis and Applications Vol. 4, No. 1, January 2006.

  12. Yao Y., Rosasco L., Caponnetto A.
    On Early Stopping in Gradient Descent Boosting. [pdf]
    Constr. Approx. 26 (2007), no. 2, 289--315.

  13. Caponnetto A., Rakhlin A.
    Some Properties of Empirical Risk Minimization over Donsker Classes. [pdf]
    Journal of Machine Learning Research (7) 2565-2583, 2006.

  14. Caponnetto A., De Vito E.
    Optimal Rates for Regularized Least-Squares Algorithm. [pdf]
    Foundations of Computational Mathematics, 7(3) 331-368, 2007.

  15. Caponnetto A., Smale S.
    Risk Bounds for Random Regression Graphs. [pdf]
    Foundations of Computational Mathematics, 7(4) 495-528, November 2007.

  16. Caponnetto A., Pontil M., De Vito E.
    Entropy Conditions for L_r-Convergence of Empirical Processes. [pdf]
    Advances in Computational Mathematics, April 2008, DOI 10.1007/s10444-008-9072-9.

  17. Caponnetto A., Pontil M., Micchelli C., Ying Y.
    Universal Multi-Task Kernels. [pdf]
    Journal of Machine Learning Research 9 (2008), 1615--1646.

  18. Li Ming, Caponnetto Andrea
    A Note on Stability of Error Bounds in Statistical Learning Theory. [pdf]
    submitted.

  19. Caponnetto A., De Vito E., Rosasco L., Verri A.
    Inverse problems perspectives on learning theory.
    in preparation.

  20. Smale S., Rosasco L., Bouvrie J., Caponnetto A., Poggio T.
    Mathematics of Neural Response. [pdf]
    Foundations of Computational Mathematics, June 2009, DOI 10.1007/s10208-009-9049-1.
    CBCL Paper #276/ CSAIL-TR #2008-070, Massachusetts Institute of Technology, Cambridge, MA, November 2008.

  21. Caponnetto A., Yao Y.
    Cross-validation based Adaptation for Regularization Operators in Learning. [pdf]
    accepted in Analysis and Applications.

Reports

  1. De Vito E., Rosasco L., Caponnetto A., Piana M., Verri A.
    Representer Theorem for Convex Loss Fuctions.
    DISI-TR-03-13, DISI, Università di Genova, 2003.

  2. De Vito E., Rosasco L., Caponnetto A., Piana M., Verri A.
    Minimization of Tikhonov Functional: the Continuous Setting.
    DISI-TR-03-14, DISI, Università di Genova, 2003.

  3. Caponnetto A., Rosasco L.
    Non Standard Support Vector Machines and Regularization Networks. [pdf]
    DISI-TR-04-03, DISI, Università di Genova, 2004.

  4. Caponnetto A., Carmeli C., De Vito E., Rosasco L., Toigo A.
    Discretization Error Analysis for Tikhonov Regularization. [pdf]
    DISI-TR-04-04, DISI, Università di Genova, 2004.

  5. Caponnetto A., De Vito E.
    Fast Rates for Regularized Least-squares Algorithm. [pdf]
    CBCL Paper #248/AI Memo #2005-013, Massachusetts Institute of Technology, Cambridge, MA, April, 2005.

  6. De Vito E., Caponnetto A.
    Risk Bounds for Regularized Least-Squares Algorithm with Operator-Valued Kernels. [pdf]
    CBCL Paper #249/AI Memo #2005-015, Massachusetts Institute of Technology, Cambridge, MA, May, 2005.

  7. Caponnetto A., Rosasco L., De Vito E., Verri A.
    Empirical Effective Dimension and Optimal Rates for Regularized Least-Squares Algorithm. [pdf]
    CBCL Paper #252/AI Memo #2005-019, Massachusetts Institute of Technology, Cambridge, MA, May 2005.

  8. Caponnetto A., Rakhlin A.
    Some Properties of Empirical Risk Minimization over Donsker Classes. [pdf]
    CBCL Paper #250/AI Memo #2005-018, Massachusetts Institute of Technology, Cambridge, MA, May 2005.

  9. Caponnetto A.
    A Note on the Role of Squared Loss in Regression. [pdf]
    CBCL Paper, Massachusetts Institute of Technology, Cambridge, MA, June 2005.

  10. Yao Y., Rosasco L., Caponnetto A.
    On Early Stopping in Gradient Descent Boosting.
    TR-2005-09, Department of Computer Science, The University of Chicago, Communicated by Partha Niyogi, 27 June 2005.

  11. Caponnetto A.
    Optimal Rates for Regularization Operators in Learning Theory. [pdf]
    CBCL Paper #264/ CSAIL-TR #2006-062, Massachusetts Institute of Technology, Cambridge, MA, 2006.

  12. Caponnetto A., Yao Y.
    Adaptation for Regularization Operators in Learning Theory. [pdf]
    CBCL Paper #265/ CSAIL-TR #2006-063, Massachusetts Institute of Technology, Cambridge, MA, 2006.

  13. Smale S., Poggio T., Caponnetto A., Bouvrie J.
    Derived Distance: towards a mathematical theory of visual cortex. [pdf]
    CBCL Paper, Massachusetts Institute of Technology, Cambridge, MA, November, 2007.

  14. Caponnetto A., Poggio T., Smale S.
    On a model of visual cortex: learning invariance and selectivity from image sequences. [pdf]
    CBCL Paper #272/ CSAIL-TR #2008-030, Massachusetts Institute of Technology, Cambridge, MA, April 4, 2008.