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20222026
most citedCyber-Twin: Digital Twin-boosted Autonomous Attack Detection for Vehicular Ad-Hoc Networks

23 citations · 58 across the 52 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

cs.NI2023

Joint SDN Synchronization and Controller Placement in Wireless Networks using Deep Reinforcement Learning

Akrit Mudvari, Leandros Tassiulas

Software Defined Networking has afforded numerous benefits to the network users but there are certain persisting issues with this technology, two of which are scalability and priva…

cs.NI2023

Adaptive Compression-Aware Split Learning and Inference for Enhanced Network Efficiency

Akrit Mudvari, Antero Vainio, Iason Ofeidis +2

The growing number of AI-driven applications in mobile devices has led to solutions that integrate deep learning models with the available edge-cloud resources. Due to multiple ben…

eess.SY2023★ 4 cited

Mobility as a Resource (MaaR) for resilient human-centric automation: a vision paper

S. Travis Waller, Amalia Polydoropoulou, Leandros Tassiulas +7

With technological advances, mobility has been moving from a product (i.e., traditional modes and vehicles), to a service (i.e., Mobility as a Service, MaaS). However, as observed…

math.OC2023★ 1 cited

Optimization methods for the capacitated refueling station location problem with routing

Nicholas Nordlund, Leandros Tassiulas, Jan-Hendrik Lange

The energy transition in transportation benefits from demand-based models to determine the optimal placement of refueling stations for alternative fuel vehicles such as battery ele…

q-fin.GN2023

Leveraging Machine Learning for Multichain DeFi Fraud Detection

Georgios Palaiokrassas, Sandro Scherrers, Iason Ofeidis +1

Since the inception of permissionless blockchains with Bitcoin in 2008, it became apparent that their most well-suited use case is related to making the financial system and its ad…

q-fin.ST2023★ 1 cited

Monetary Policy, Digital Assets, and DeFi Activity

Antzelos Kyriazis, Iason Ofeidis, Georgios Palaiokrassas +1

This paper studies the effects of unexpected changes in US monetary policy on digital asset returns. We use event study regressions and find that monetary policy surprises negative…