Akhiezer NI, Glazman IM. (1993). Theory of linear operators in Hilbert spaces. 1
Amodei L. (1997). Reproducing kernels of vector-valued function spaces Curves and Surfaces: Proceedings of Chamonix 1996.
Aronszajn N. (1950). Theory of reproducing kernels Transactions Of The American Mathematical Society. 68
Baldi P, Frasconi P, Pollastri G, Vullo A. (2002). New machine learning methods for the prediction of protein topologies Artificial intelligence and heuristic methods for bioinformatic.
Bennett KP, Embrechts MJ. (2003). An optimization perspective on partial least squares Advances in kearning theory: Methods, models, and applications.
Berberian SK. (1966). Notes on spectral theory.
Beymer D, Poggio T. (1996). Image representations for visual learning. Science (New York, N.Y.). 272 [PubMed]
Burbea J, Masani P. (1984). Banach and Hilbert spaces of vector-valued functions.
Cressie NAC. (1993). Statistics for spatial data.
Csato L, Opper M, Cornford D, Evans D. (2004). Bayesian analysis of the scatterometer wind retrieval inverse Problem: Some new approaches J Royal Stat Soc B. 66
Evgeniou T, Pontil M. (2004). Regularized multi-task learning Proc. of the 10th ACM SIGKOD Int. Conf. on Knowledge Discovery and Data Mining.
Fillmore PA. (1970). Notes on operator theory.
Franke U et al. (1998). Autonomous driving goes downtown IEEE Intelligent Systems. 13
Friedman J, Breiman L. (1997). Predicting multivariate responses in multiple linear regression (with discussion) J Roy Statist Soc B. 59
Mangasarian OL. (1994). Nonlinear programming.
Mangasarian OL, Bennett KP. (1993). Multicategory discrimination via linear programming Optimization Methods And Software. 3
Micchelli CA. (1995). Mathematical aspects of geometric modeling.
Micchelli CA, Fitzgerald CH, Pinkus AM. (1995). Functions that preserve families of positive definite functions Linear Algebra And Its Applications. 221
Micchelli CA, Melkman AA. (1979). Optimal estimation of linear operators in Hilbert spaces from inaccurate data SIAM Journal Of Numerical Analysis. 16
Mulier F, Cherkassky V. (1998). Learning from data: Concepts, theory, and methods.
Poggio T, Evgeniou T, Pontil M. (2000). Regularization networks and support vector machines Adv Comp Math. 13
Pontil M, Micchelli CA. (2003). On learning vector-valued functions Research Note No. RN-03-08.
Pontil M, Micchelli CA. (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
Scholkopf B, Smola AJ. (2001). Learning with kernels: Support vector machines, regularization, optimization, and beyond.
Scholkopf B, Weston J, Chapelle O, Elisseeff A, Vapnik VN. (2003). Kernel dependency estimation Advances in neural information processing Systems. 15
Sejnowski TJ, Rosenberg CR. (1987). Parallel networks which learn to pronounce English text Complex Systems. 1
Shawe-taylor J, Cristianini N. (2000). An introduction to support vector machines.
Singer Y, Cramer K. (2001). On the algorithmic implementation of multiclass kernel-based vector machines J Mach Learn Res. 2
Tibshirani R, Hastie T, Friedman J. (2001). The elements of statistical learning.
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, 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