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This article studies the problem of reconstructing the topology of a network of interacting agents via observations of the state-evolution of the agents. We focus on the large-scale network setting with the additional constraint of partial observations, wh ...
In Environmental Impact Assessment (EIA), the either positive or negative impacts that specific N project actions might generate on a number M of environmental components are typically summarized in the form of Interaction Matrix (IM). This is an NxM tabul ...
Datacenters are the heart of our digital lives. Online applications, such as social-networking and e-commerce, run inside datacenters under strict Service Level Objectives for their tail latency. Tight latency SLOs are necessary for such services to remain ...
The paper “Dynamic efficiency in multilayer transportation networks” (Bellocchi, Geroliminis, 2018) [1] introduced new performance measures to quantify dynamically the effect of traffic congestion in a multilayer network. Based on these measures, we explor ...
We develop a model that successfully learns social and organizational human network structure using ambient sensing data from distributed plug load energy sensors in commercial buildings. A key goal for the design and operation of commercial buildings is t ...
Braided rivers form some of the most fascinating fluvial patterns found on Earth. They are identifiable by their unique morphology of complex networks of intertwined channels that spread across wide floodplains. Detailed knowledge of their dynamics is need ...
We consider the general problem of describing the dynamics of subnetworks of larger biochemical reaction networks, e.g., protein interaction networks involving complex formation and dissociation reactions. We propose the use of model reduction strategies t ...
Realistic rendering using discrete reflectance measurements is challenging, because arbitrary directions on the light and view hemispheres are queried at render time, incurring large memory requirements and the need for interpolation. This explains the des ...
We present an efficient and accurate people detection approach based on deep learning to detect people attacks and intrusion in video surveillance scenarios Unlike other approaches using background segmentation and pre-processing techniques, which are not ...
We present a novel method for semantic text document analysis which in addition to localizing text it labels the text in user-defined semantic categories. More precisely, it consists of a fully-convolutional and sequential network that we apply to the part ...
