Regularization, Optimization, Kernels, and Support Vector Machines offers a snapshot of the current state of the art of...... more

, dynamic models that contain neural network architectures might be highly non-linear and difficult to analyse as a result...... more

reflecting a great variety of reasoning tasks in the sciences. This volume reflects the multi-dimensional nature of the interplay...... more

kernel version as a one-class modelling problem. This leads to new primal-dual support vector machine formulations for kernel...... more

, dynamic models that contain neural network architectures might be highly non-linear and difficult to analyse as a result...... more

This four volume set, edited and authored by world leading experts, gives a review of the principles, methods and...... more

This first volume, edited and authored by world leading experts, gives a review of the principles, methods and...... more

, chaos and synchronization. Cellular neural networks and their universal machine implementations offer a well-established...... more