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Spatial autocorrelation is a parameter of importance for network data analysis. To estimate spatial autocorrelation, maximum likelihood has been popularly used. However, its rigorous implementation re...
Modern data acquisition routinely produces massive amounts of network data.Though many methods and models have been proposed to analyze such data, the research of network data is largely disconnected ...
Modern data acquisition routinely produces massive amounts of network data.Though many methods and models have been proposed to analyze such data, the research of network data is largely disconnected ...
This paper describes a new adaptive algorithm that smoothly and dynamically adjusts the system resources of link rates and transmitter powers to maximize the performance of the system. Performance is ...
We present a distributed cross layer approach to controlling the network performance under various QoS requirements in interference limited systems. The interaction between the different layers of the...
We describe a specialized truncated Newton primal-dual interior-point method that solves large scale network utility maximization problems, with concave utility functions, efficiently and reliably. Ou...
We consider a multi-period variation of the network utility maximization problem that includes delivery constraints. We allow the flow utilities, link capacities and routing matrices to vary over time...
Recently, a semidefinite programming (SDP) relaxation approach has been proposed to solve the sensor network localization problem. Although it achieves high accuracy in estimating the sensor locations...
Gene regulatory networks capture interactions between genes and other cell substances, resulting in various models for the fundamental biological process of transcription and translation. The expressi...
We present a crosslayer technique to find and characterize optimal control policies for wireless networks operating at different time scales at the upper layer and physical layer. The technique can al...
We consider a network of devices, such as generators, fixed loads, deferrable loads, and storage devices, each with its own dynamic constraints and objective, connected by AC and DC lines. The problem...
Convex optimization is an essential tool for modern data analysis, as it provides a framework to formulate and solve many problems in machine learning and data mining. However, general convex optimiza...
A diffusion approximation for a network of continuous time reservoirs with power law release rules is examined. Under a mild assumption on the inflow processes, we show that for physically reasonable ...
In a multiclass network of queues, natural sufficient conditions are given for the mean number-in-system vector to cover the nonnegative orthant as the arrival rate vector varies over the stable domai...
Collaboration is important to successful organizations and how coworkers are selected is crucial to the dynamics of effective collaborations. In this study we explore how people use social netwo...

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