Nucleon-antinucleon Interaction from the Modified Skyrme Model

We calculate the static nucleon-antinucleon interaction potential from the modified Skyrme model with additional $B^{\mu}B_{\mu}$ term using the product ansatz. The static properties of single baryon are improved in the modified Skyrme model. State mixing is taken into account by perturbation theory, which substantially increases the strength of the central attraction. We obtain a long and mid range potential which is in qualitative agreement with some phenomenological potentials.Comment: 21 pages, 7 figur

Iterative Regularization for Learning with Convex Loss Functions

We consider the problem of supervised learning with convex loss functions and propose a new form of iterative regularization based on the subgradient method. Unlike other regularization approaches, in iterative regularization no constraint or penalization is considered, and generalization is achieved by (early) stopping an empirical iteration. We consider a nonparametric setting, in the framework of reproducing kernel Hilbert spaces, and prove finite sample bounds on the excess risk under general regularity conditions. Our study provides a new class of efficient regularized learning algorithms and gives insights on the interplay between statistics and optimization in machine learning