This paper considers distributed nonconvex optimization with the cost functions being distributed over agents. Noting that information compression is a key tool to reduce the heavy communication load for distributed a...
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Dexterous manipulation, which refers to the ability of a robotic hand or multi-fingered end-effector to skillfully control, reorient, and manipulate objects through precise, coordinated finger movements and adaptive f...
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Recursive identification of structured multivariate models is known to be difficult due to the general non-convexity of the likelihood function. In this work, we propose a recursive multivariate weighted null-space fi...
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Recursive identification of structured multivariate models is known to be difficult due to the general non-convexity of the likelihood function. In this work, we propose a recursive multivariate weighted null-space fitting method for identification of structured multivariate models. The proposed method first uses recursive least squares to estimate a high order non-parametric model, then a parametric model is obtained through weighted least squares from the non-parametric model. In this way, the method avoids directly optimizing a non-convex likelihood function and has guaranteed global convergency. Moreover, the proposed method is flexible in model structures and has the same finite sample performance as its off-line counterpart. We use simulation examples to illustrate the performance.
In this paper, we consider a stochastic distributed nonconvex optimization problem with the cost function being distributed over n agents having access only to zeroth-order (ZO) information of the cost. This problem h...
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This paper considers the distributed online convex optimization problem with time-varying constraints over a network of agents. This is a sequential decision making problem with two sequences of arbitrarily varying co...
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Nowadays, social networks have become an important part of our daily lives. Hence, several researchers have been interested in the study and analysis of the interactions between the entities composing this type of net...
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This paper considers online convex optimization with long term constraints, where constraints can be violated in intermediate rounds, but need to be satisfied in the long run. The cumulative constraint violation is us...
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A novel engineering model reduction method is proposed in this paper that can be applied to a chemical reaction network (CRN) with chains of linear reactions. The reduced model is a delayed CRN with possibly different...
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In this paper CRNs containing linear reaction chains with multiple joint complexes were considered in order to obtain an equivalent reduced order delayed CRN model with distributed time delays. For this purpose, our e...
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In this paper CRNs containing linear reaction chains with multiple joint complexes were considered in order to obtain an equivalent reduced order delayed CRN model with distributed time delays. For this purpose, our earlier method (Lipták and Hangos (2018)) for decomposing the chains of linear reactions with multiple joint complexes was used together with the "linear chain trick". An analytical expression for the kernel function of the distributed delay was also derived from the reaction rate coefficients of the linear reaction chains. Our approach was demonstrated using the example of the well known McKeithan’s network model of kinetic proofreading.
The distributed nonconvex optimization problem of minimizing a global cost function formed by a sum of n local cost functions by using local information exchange is considered. This problem is an important component o...
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