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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 ...
Structural Health Monitoring (SHM) has greatly benefited from computer vision. Recently, deep learning approaches are widely used to accurately estimate the state of deterioration of infrastructure. In this work, we focus on the problem of bridge surface s ...
In the celebrated coded caching problem studied by Maddah-Ali and Niesen, the peak-traffic network load is to be reduced by first caching some information about contents into individual memories of end users during the off-peak hours and then upon user req ...
Brain mechanisms of visual selective attention involve both local and network-level activity changes at specific oscillatory rhythms, but their interplay remains poorly explored. Here, we investigate anticipatory and reactive effects of feature-based atten ...
In this paper we study the properties of the quenched pressure of a multi-layer spin-glass model (a deep Boltzmann Machine in artificial intelligence jargon) whose pairwise interactions are allowed between spins lying in adjacent layers and not inside the ...
The integrated network Mott Physics Beyond the Heisenberg Model (MPBH) united researchers across Switzerland in a collective effort to explore new aspects of Mott physics, in particular how spin-orbit interactions, in concert with strong electron correlati ...
Recent trends in shipboard power distribution network design, such as the transition from AC to DC result in new challenges on the issue of distribution network protection. Devices such as a solid state bus tie switch provide a first line of defence agains ...
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 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 ...
We consider the problem of path inference: given a path prefix, i.e., a partially observed sequence of nodes in a graph, we want to predict which nodes are in the missing suffix. In particular, we focus on natural paths occurring as a by-product of the int ...
