A single cut proximal bundle method for stochastic convex composite optimization

In this paper, we consider optimization problems where the objective is the sum of a function given by an expectation and a Lipschitz continuous convex function. For such problems, we propose a Stochastic Composite Proximal Bundle (SCPB) method with optimal complexity. The method does not require estimation of parameters involved in the assumptions on the objective functions. Moreover, to the best of our knowledge, this is the first proximal bundle method for stochastic programming able to deal with continuous distributions. Finally, we present the results of numerical experiments where SCPB slightly outperforms Stochastic Mirror Descent.Comment: 23 page

Extended field-of-view in a lensless endoscope using an aperiodic multicore fiber

We investigate lensless endoscopy using coherent beam combining and aperiodic multicore fibers (MCF). We show that diffracted orders, inherent to MCF with periodically arranged cores, dramatically reduce the field of view (FoV) and that randomness in MCF core positions can increase the FoV up to the diffraction limit set by a single fiber core, while maintaining MCF experimental feasibility. We demonstrate experimentally pixelation-free lensless endoscopy imaging over a 120 micron FoV with an aperiodic MCF designed with widely spaced cores. We show that this system is suitable to perform beam scanning imaging by simply applying a tilt to the proximal wavefront.Comment: Submitted to Optics Letter