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We consider a problem of information structure design in team decision problems and team games. We propose simple, scalable greedy algorithms for adding a set of extra information links to optimize team performance and resilience to non-cooperative and adv ...
We consider L1 -TV regularization of univariate signals with values on the real line or on the unit circle. While the real data space leads to a convex optimization problem, the problem is nonconvex for circle-valued data. In this paper, we deriv ...
The gasification of highly watered waste residues may help to reduce fossil fuels consumption, as well as emissions, all the while improving efficiency. The integration of supercritical gasification with solar energy may improve the performances of both ne ...
The fully connected conditional random field (CRF) with Gaussian pairwise potentials has proven popular and effective for multi-class semantic segmentation. While the energy of a dense CRF can be minimized accurately using a linear programming (LP) relaxat ...
This paper provides expressions for the largest and smallest solution of a global optimization problem using an adjoint variable which represents the available one-sided improvements up to the interval “horizon”. Interpreting the problem in terms of optima ...
This paper presents an integrated approach for short-term supply chain management (SCM) at a fast moving consumer goods production plant. The problem is to determine the production quantities, to provide a detailed production schedule, to trigger the relev ...
The goal of query optimization is to map a declarative query (describing data to generate) to a query plan (describing how to generate the data) with optimal execution cost. Query optimization is required to support declarative query interfaces. It is a co ...
During the last decade, there has been an increasing trend to combine customer behavior models in optimization, since it provides a better understanding of the preferences of clients to policy makers while planning for their systems. These preferences are ...
The performance of evolutionary algorithms can be heavily undermined when constraints limit the feasible areas of the search space. For instance, while Covariance Matrix Adapta- tion Evolution Strategy is one of the most efficient algorithms for unconstrai ...
Institute of Electrical and Electronics Engineers2016
This thesis contributes towards the design and analysis of fast and distributed optimization algorithms based on splitting techniques, such as proximal gradient methods or alternation minimization algorithms, with the application of solving model predictiv ...
