We study the problem of multivariate integration over Rd with integrands of the form f(x)d(x) where d is a probability density function. Practical problems of this form occur comm...
Frances Y. Kuo, Grzegorz W. Wasilkowski, Benjamin ...
The reconstruction problem is usually formulated as a variational problem in which one searches for that image that minimizes a so called prior (image model) while insisting on cer...
Bart Janssen, Remco Duits, Bart M. ter Haar Romeny
In this paper, we consider the problem of planning and learning in the infinite-horizon discounted-reward Markov decision problems. We propose a novel iterative direct policysearc...
We consider the least-square regression problem with regularization by a block 1-norm, that is, a sum of Euclidean norms over spaces of dimensions larger than one. This problem, r...
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...