Journal: Adv. Comput. Math.

Volume 13, Issue 4

335 -- 354Martin Burger, Heinz W. Engl. Training neural networks with noisy data as an ill-posed problem
355 -- 373Oleg Davydov, Larry L. Schumaker. Locally linearly independent bases for bivariate polynomial spline spaces
375 -- 386Xiu Ye. Stabilized finite element approximations for the Reissner-Mindlin plate
387 -- 403Hrushikesh Narhar Mhaskar, Francis J. Narcowich, Jürgen Prestin, Joseph D. Ward. Polynomial frames on the sphere
405 -- 415Zdzislaw Jackiewicz, Arne Marthinsen, Brynjulf Owren. Construction of Runge-Kutta methods of Crouch-Grossman type of high order

Volume 13, Issue 3

199 -- 229Rida T. Farouki, Hwan Pyo Moon, Bahram Ravani. Algorithms for Minkowski products and implicitly-defined complex sets
231 -- 256Lucas Jódar, Marco Marletta. Solving ODEs arising from non-selfadjoint Hamiltonian eigenproblems
257 -- 270Kevin Burrage, H. Suhartanto. Parallel iterated methods based on variable step-size multistep Runge - Kutta methods of Radau type for stiff problems
271 -- 292J. Lorente-Pardo, Paul Sablonnière, M. C. Serrano-Pérez. On the convexity of ::::C:::::::1::: surfaces associated with some quadrilateral finite elements
293 -- 318E. Venturino, G. A. Chandler. Calculation of line integrals in boundary integral methods
319 -- 333Say Song Goh, Chee Heng Yeo. Uncertainty products of local periodic wavelets

Volume 13, Issue 2

105 -- 129Sven Ehrich. On the estimation of wavelet coefficients
131 -- 165Di-Rong Chen, Bin Han 0003, Sherman D. Riemenschneider. Construction of multivariate biorthogonal wavelets with arbitrary vanishing moments
167 -- 198Lutz Angermann. Error analysis of upwind-discretizations for the steady-state incompressible Navier-Stokes equations

Volume 13, Issue 1

1 -- 50Theodoros Evgeniou, Massimiliano Pontil, Tomaso Poggio. Regularization Networks and Support Vector Machines
51 -- 77I. Ben Salah, P. Maroni. The connection between self-associated two-dimensional vector functionals and third degree forms
79 -- 103Vitaly Maiorov, Ron Meir. On the near optimality of the stochastic approximation of smooth functions by neural networks