working papers

1. De Mol, C., De Vito E. and Rosasco L.
   "Elastic Net Regularization in Learning Theory",
2. De Vito, E. and Pereverzev S. and Rosasco L.
   "Adaptive Learning via the Balancing Principle"
3. Belkin, M., De Vito, E. and Rosasco, L.
   "Random Estimates of Operators and their Spectral Properties for Learning."

journal papers

1. Lo Gerfo L., Rosasco L., Odone F., De Vito E. and Verri, A.
   "Spectral Algorithms for Supervised Learning",
   to appear in Neural Computation.
2. Bauer F., Pereverzev S. and Rosasco L.
   "On Regularization Algorithms in Learning Theory",
   J. Complexity 23(1): 52-72 (2007) (Technical Report DISI-TR-05-19).
3. Yao Y., Rosasco L. and Caponnetto, A.
   "On Early Stopping in Gradient Descent Learning",
   Constr. Approx. 26 (2007), no. 2, 289–315.
4. De Vito E., Rosasco L. and Caponnetto, A.
   " Discretization Error Analysis for Tikhonov Regularization ",
   Analysis and Applications Vol. 4, No. 1 (January 2006).
5. De Vito E., Rosasco L.,Caponnetto A., De giovannini U. and Odone F.
   " Learning from Examples as an Inverse Problem ",
   Journal of Machine Learning Research 6(May):883--904, 2005.
6. De Vito E., Rosasco L., Caponnetto A., Piana M. and Verri A.
   " Some Properties of Regularized Kernel Methods",
   Journal of Machine Learning Research 5(Oct):1363--1390, 2004. .
7. De Vito E., Caponnetto A, Rosasco L..
   " Model Selection for Regularized Least-Squares Algorithm in Learning Theory",
   Foundations of Computational Mathematics Volume 5, Number 1 pp. 59 - 85, February 2005 .
8. Rosasco L., Caponnetto A., De Vito E., Piana M. and Verri A.
   " Are Loss Function All the Same?"
   Neural Computation, Vol. 16, Issue 5 - May 2004.

conference papers

1. Barla, A., Mosci, S., Rosasco, L. and Verri, A.
   "A method for robust variable selection wit significance assessments"
   16th European Symposium on Artificial Neural Networks.
2. Mosci, S., Rosasco, L. and Verri A.
   " Dimensionality reduction and generalization ",
   ACM International Conference Proceeding Series; Vol. 227 archive Proceedings of the 24th International Conference on Machine Learning
3. Caponnetto A., Rosasco L., Odone F. and Verri A.
   " Support Vectors Algorithms as Regularization Networks ",
   13th European Symposium on Artificial Neural Networks.
4. Rosasco L., Caponnetto A., De Vito E., De giovannini U. and Odone F.
   " Learning, Regularization and Ill-posed Inverse problems ",
   Eighteenth Annual Conference on Neural Information Processing Systems.

technical reports

1. Rosasco L., De Vito E. and Verri A.
   " Spectral Methods for Regularization in Learning Theory",
   Technical report DISI-TR-05-18.
2. Caponnetto A., Rosasco L., De Vito E. and Verri A.
   "Empirical Effective Dimension and Optimal Rates for Regularized Least Squares Algorithm ",
   CBCL Paper #252/AI Memo #2005-019, MIT, Cambridge, MA, May 2005.
3. Caponnetto A. and Rosasco L.
   " Non Standard Support Vector Machines and Regularization Networks",
   DISI-TR-04-03.
4. De Vito E., Rosasco L., Caponnetto A., Piana M. and Verri A.
   "Representer Theorem for Convex Loss Fuction",
   DISI-TR-03-13.
5. De Vito E., Rosasco L., Caponnetto A., Piana M. and Verri A.
   " Minimization of Tiklhonov Functional: the Continuos Setting",
   DISI-TR-03-14 .