Haze often limits visibility and reduces contrast in outdoor images. The degradation varies
spatially since it depends on the objects' distances from the camera. This dependency is …

Energy storage can play an important role in energy management of end users. To promote
an efficient utilization of energy storage, we develop a novel business model to enable …

Optimization is one of the most important areas of modern applied mathematics, with
applications in fields from engineering and economics to finance, statistics, management …

Interior point methods for optimization have been around for more than 25 years now. Their
presence has shaken up the field of optimization. Interior point methods for linear and …

We propose a novel algorithm for monocular depth estimation using relative depth maps.
First, using a convolutional neural network, we estimate relative depths between pairs of …

Non-traditional laser and fluid jet processes exhibit time-dependent material removal
characteristics. The feedrate profile must be planned carefully along the toolpath for …

We present a scalable approach and implementation for solving stochastic optimization
problems on high-performance computers. In this work we revisit the sparse linear algebra …

The fundamental challenge of the origin-destination (OD) matrix estimation problem is that it
is severely under-determined. In this paper we propose a new data driven OD estimation …

The Bayesian earthquake analysis tool (BEAT) is an open‐source Python software to
conduct source‐parameter estimation studies for crustal deformation events, such as …

We consider numerical methods for finding (weak) second-order critical points for large-
scale non-convex quadratic programming problems. We describe two new methods. The …