12 citations · 18 across the 3 of their papers we have counts for
6 papers
Combining Relevance and Magnitude for Resource-Aware DNN Pruning
Carla Fabiana Chiasserini, Francesco Malandrino, Nuria Molner +1
Pruning neural networks, i.e., removing some of their parameters whilst retaining their accuracy, is one of the main ways to reduce the latency of a machine learning pipeline, espe…
Choose, not Hoard: Information-to-Model Matching for Artificial Intelligence in O-RAN
Jorge Martín-Pérez, Nuria Molner, Francesco Malandrino +3
Open Radio Access Network (O-RAN) is an emerging paradigm, whereby virtualized network infrastructure elements from different vendors communicate via open, standardized interfaces.…
Network Support for High-performance Distributed Machine Learning
Francesco Malandrino, Carla Fabiana Chiasserini, Nuria Molner +1
The traditional approach to distributed machine learning is to adapt learning algorithms to the network, e.g., reducing updates to curb overhead. Networks based on intelligent edge…
Delay and reliability-constrained VNF placement on mobile and volatile 5G infrastructure
Balázs Németh, Nuria Molner, Jorge Jorge Martín-Pérez +3
The ongoing research and industrial exploitation of SDN and NFV technologies promise higher flexibility on network automation and infrastructure optimization. Choosing the location…
Arbitration Among Vertical Services
Claudio Casetti, Carla Fabiana Chiasserini, Nuria Molner +6
A 5G network provides several service types, tailored to specific needs such as high bandwidth or low latency. On top of these communication services, verticals are enabled to depl…
Resource Orchestration of 5G Transport Networks for Vertical Industries
K. Antevski, J. Martín-Pérez, Nuria Molner +12
The future 5G transport networks are envisioned to support a variety of vertical services through network slicing and efficient orchestration over multiple administrative domains.…