We investigate a fast optimization method for determining the minimizer of the negative Poisson likelihood function for the global analysis of fluorescence lifetime microscopy. Using the alternating optimization strategy, we iteratively solve a non-convex optimization problem to estimate the lifetime parameters and a convex optimization problem to estimate the concentration parameters. We effec...

Coordinate descent is a general strategy for convex optimization problems. The basic idea is iteratively solve the problem by optimizing the objective only with respect to one optimization variable at a time while keeping all other dimensions fixed. While the order in which the dimensions are optimized can be chosen arbitrarily, it is crucial for convergence guarantees that updates occur sequen...

For many problems from science and engineering it is impractical to perform experiments on the physical world directly (e.g., airfoil design, earthquake propagation). Instead, complex, physics-based simulation codes are used to run experiments on computer hardware. While allowing scientists more flexibility to study phenomena under controlled conditions, computer experiments require a substanti...

Specializing programs with respect to run-time values is an optimization strategy that has been shown to drastically improve code performance on realistic programs ranging from operating systems to graphics. Recently, various approaches to specializing code at run-time have been proposed. However, these approaches still suuer from shortcomings that limit their applicability: they are either man...

Contrast-enhanced digital breast tomosynthesis (CE-DBT) uses an iodinated contrast agent to image the threedimensional breast vasculature. The University of Pennsylvania is conducting a CE-DBT clinical study in patients with known breast cancers. The breast is compressed continuously and imaged at four time points (1 pre-contrast; 3 postcontrast). A hybrid subtraction scheme is proposed. First,...

In this paper, we propose a simple yet effective heuristic framework called Fragmental Optimization (FO). In FO, there are two tightly coupled elements: Fragment Selection and Optimization. We formulate the FO technique and apply it to the 2-machine bicriteria flowshop scheduling problem and the 3-Index Assignment Problem. We conduct extensive experiments on standard benchmark instances for the...