8 accepted papers
This letter investigates the target search problem for a network of autonomous vehicles, aiming to maximize the detection of randomly appearing targets within a given area. Considering no prior knowledge of the targets is available, we propose a multi-vehicle cooperative persistent coverage scheme u
Meta-learning empowers data-hungry deep neural networks to rapidly learn from merely a few samples, which is especially appealing to tasks with small datasets. Critical in this context is the *prior knowledge* accumulated from related tasks. Existing meta-learning approaches typically rely on presel…
Deep neural networks (DNNs) have well-documented merits in learning nonlinear functions in high-dimensional spaces. Stochastic gradient descent (SGD)-type optimization algorithms are the ‘workhorse’ for training DNNs. Nonetheless, such algorithms often suffer from slow convergence, sizable fluctuati…
Conditional gradient, aka Frank Wolfe (FW) algorithms, have well-documented merits in machine learning and signal processing applications. Unlike projection-based methods, momentum cannot improve the convergence rate of FW, in general. This limitation motivates the present work, which deals with hea…
Wireless and wireline networks, such as Internet, cellular, and content delivery networks are to serve end-user file requests proactively. To this aim, by storing anticipated highly popular files during off-peak periods, and fetching them to end-users during on-peak instances, these networks smoothe…
Next-generation communication networks are envisioned to extensively utilize storage-enabled caching units to alleviate unfavorable surges of data traffic by pro-actively storing anticipated highly popular contents across geographically distributed storage devices during off-peak periods. This resou…
In next generation cellular networks (5G) the access points (APs) are anticipated to be equipped with storage devices to serve locally requests for reusable popular contents by caching them at the edge of the network. The ultimate goal is to shift part of the load on the back-haul links from on-peak…