Akhiezer NI, Glazman IM (1993) Theory of linear operators in Hilbert spaces

Amodei L (1997) Reproducing kernels of vector-valued function spaces Curves and Surfaces: Proceedings of Chamonix 1996, Le Meehaute A:Rabut C:Schumaker LL, ed.

Aronszajn N (1950) Theory of reproducing kernels Transactions Of The American Mathematical Society 68:337-404

Baldi P, Pollastri G, Frasconi P, Vullo A (2002) New machine learning methods for the prediction of protein topologies Artificial intelligence and heuristic methods for bioinformatic, Frasconi P:Shamire R, ed.

Bennett KP, Embrechts MJ (2003) An optimization perspective on partial least squares Advances in kearning theory: Methods, models, and applications, Suykens J:Horrath G:Basu S:Miccelli C:Vandewalle J, ed. pp.277

Bennett KP, Mangasarian OL (1993) Multicategory discrimination via linear programming Optimization Methods And Software 3:722-734

Berberian SK (1966) Notes on spectral theory

Beymer D, Poggio T (1996) Image representations for visual learning. Science 272:1905-9 [PubMed]

Breiman L, Friedman J (1997) Predicting multivariate responses in multiple linear regression (with discussion) J Roy Statist Soc B 59:3-37

Burbea J, Masani P (1984) Banach and Hilbert spaces of vector-valued functions

Cherkassky V, Mulier F (1998) Learning from data: Concepts, theory, and methods

Cornford D, Csato L, Evans D, Opper M (2004) Bayesian analysis of the scatterometer wind retrieval inverse Problem: Some new approaches J Royal Stat Soc B 66:1-17

Cramer K, Singer Y (2001) On the algorithmic implementation of multiclass kernel-based vector machines J Mach Learn Res 2:265-292

Cressie NAC (1993) Statistics for spatial data

Cristianini N, Shawe-taylor J (2000) An introduction to support vector machines

Evgeniou T, Pontil M (2004) Regularized multi-task learning Proc. of the 10th ACM SIGKOD Int. Conf. on Knowledge Discovery and Data Mining

Evgeniou T, Pontil M, Poggio T (2000) Regularization networks and support vector machines Adv Comp Math 13:1-50

Fillmore PA (1970) Notes on operator theory

Fitzgerald CH, Micchelli CA, Pinkus AM (1995) Functions that preserve families of positive definite functions Linear Algebra And Its Applications 221:83-102

Franke U, Gavrila D, Goerzig S, Lindner F, Paetzold F, Woehler C (1998) Autonomous driving goes downtown IEEE Intelligent Systems 13:40-48

Hastie T, Tibshirani R, Friedman J (2001) The elements of statistical learning

Mangasarian OL (1994) Nonlinear programming

Melkman AA, Micchelli CA (1979) Optimal estimation of linear operators in Hilbert spaces from inaccurate data SIAM Journal Of Numerical Analysis 16:87-105

Micchelli CA (1995) Mathematical aspects of geometric modeling

Micchelli CA, Pontil M (2003) On learning vector-valued functions Research Note No. RN-03-08

Micchelli CA, Pontil M (2004) A function representation for learning in Banach spaces Proceedings of the Seventeenth Annual Conference on Learning Theory

Rosipal R, Trejo LJ (2001) Kernel partial least squares regression in reproducing kernel Hilbert spaces J Mach Learn Res 2:97-123

Scholkopf B, Smola AJ (2001) Learning with kernels: Support vector machines, regularization, optimization, and beyond

Sejnowski TJ, Rosenberg CR (1987) Parallel networks which learn to pronounce English text Complex Systems 1:145-163

Tikhonov AN, Arsenin VY (1977) Solution of ill-posed problems

Vapnik V (1998) Statistical Learning Theory

Wahba G (1990) Splines models for observational data

Weston J, Chapelle O, Elisseeff A, Scholkopf B, Vapnik VN (2003) Kernel dependency estimation Advances in neural information processing Systems

Weston J, Watkins C (1998) Multi-class support vector machines Tech. Rep. No. CSD-TR-98-04

Williams CKI, Barber D (1998) Bayesian classification with gaussian processes IEEE Trans Patt Anal Mach Intel 20:1342-1351