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The least absolute shrinkage and selection operator (LASSO) for linear regression exploits the geometric interplay of the ℓ2-data error objective and the ℓ1-norm constraint to arbitrarily select sparse models. Guiding this uninformed selection ...
Our contribution in this paper is two fold. First, we propose a novel discretization of the forward model for differential phase-contrast imaging that uses B-spline basis functions. The approach yields a fast and accurate algorithm for implementing the for ...
Our contribution in this paper is two fold. First, we propose a novel discretization of the forward model for differential phase-contrast imaging that uses B-spline basis functions. The approach yields a fast and accurate algorithm for implementing the fo ...
Traditional local approaches to continuum damage mechanics are known to lead to mesh dependency due to damage localization. Some corrections for this ill-posed problem exist through localization limiters. The integral non-local regularization is widely use ...
The recent advances in fluorescent molecular probes, photon detection instrumentation, and photon propagation models in tissue, have facilitated the emergence of innovative molecular imaging technologies such as Fluorescence Diffuse Optical Tomography (FDO ...
We develop a principled way of identifying probability distributions whose independent and identically distributed realizations are compressible, i.e., can be well approximated as sparse. We focus on Gaussian compressed sensing, an example of underdetermin ...
In this paper we consider the problem of recovering a high dimensional data matrix from a set of incomplete and noisy linear measurements. We introduce a new model that can efficiently restrict the degrees of freedom of the problem and is generic enough to ...
Institute of Electrical and Electronics Engineers2012
In this paper we consider recovery of a high dimensional data matrix from a set of incomplete and noisy linear measurements. We introduce a new model which can efficiently restricts the degrees of freedom of data and, at the same time, is generic so that f ...
We consider the assignment of gates to arriving and departing flights at a large hub airport. It is considered to be a highly complex problem even in planning stage when all flight arrivals and departures are assumed to be known precisely in advance. There ...
The recent availability of whole-genome sequencing data affords tremendous power for statistical inference. With this, there has been great interest in the development of polymorphism-based approaches for the estimation of population genetic parameters. Th ...
