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In this talk, we discuss a unifying deep unfolding multi-sampling-ratio interpretable CS-MRI framework. The combined approach offers more generalizability than the existing deep-learning-based CS-MRI ...
We focus on the nonconvex-strongly-convex bilevel optimization problem (BLO). In this BLO, the objective function of the upper-level problem is nonconvex and possibly nonsmooth, and the lower-level pr...
Tensor-based modeling and computation emerge prominently with urgent demands from practical applications in the big data era. With the intrinsic sparsity in real data sets and the dimensionality reduc...
Sparsity is a naturally occurring characteristic in many real-world applications including signal denoising, outlier detection, and finance. On one hand, sparsity assumption allows people to tackle in...
Zero-One Composite Optimization (0/1-COP) is a prototype of nonsmooth, non- convex optimization problems and it has attracted much attention recently. Augmented Lagrangian Method (ALM) has stood out a...
Nonconvex constrained optimization (NCO) has been one of the important research fields in optimization community. It has widely appeared in many application fields. However, challenges for solving NCO...
In electronic structure calculations, Kohn-Sham equations rank among the most widely adopted mathematical models. However, due to the deficiency of available approximations for exchange-correlation en...
Unlike traditional robust optimization, personalized optimization aims to find the values of control variables that yield the optimal value of the objective function for given values of environmental ...
This talk concerns the nonsmooth distributed optimization problem via multi-agent network with the coupled equality and inequality constraints. The considered global optimization problem is to minimiz...
Reliability of a system conveys information about the absence of failures, and is usually define as the probability that the system will perform its intended function for a specified time period when ...
The 2017 American Control Conference will be held Wednesday through Friday, May 24-26 at the Sheraton Seattle Hotel, centrally located in the heart of downtown Seattle, WA. Sheraton Seattle Hotel is n...
Graph theory and discrete optimization are fundamental subjects in the fields of information theory, data analysis, network study and communication, and they have been applied widely in information te...
The International Conference on Numerical Analysis, approximation and Optimization will be held in Beijing, August 5-7, 2016. The conference highlights recent advances in Numerical Analysis, Approxima...
The problem of optimizing the H_infinity norm of a rational transfer matrix with respect to a finite number of design parameters is considered. The H_infinity norm is characterized as a value of a par...
In this tutorial, an approach to the analysis and design of linear control systems based on numerical convex optimization over closed-loop maps is presented. Convexity makes numerical solution effecti...

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