68 citations · 148 across the 13 of their papers we have counts for
14 papers
Workflow Optimization for Parallel Split Learning
Joana Tirana, Dimitra Tsigkari, George Iosifidis +1
Split learning (SL) has been recently proposed as a way to enable resource-constrained devices to train multi-parameter neural networks (NNs) and participate in federated learning…
MP-SL: Multihop Parallel Split Learning
Joana Tirana, Spyros Lalis, Dimitris Chatzopoulos
Federated Learning (FL) stands out as a widely adopted protocol facilitating the training of Machine Learning (ML) models while maintaining decentralized data. However, challenges…
Lightweight Modeling of User Context Combining Physical and Virtual Sensor Data
Mattia Giovanni Campana, Dimitris Chatzopoulos, Franca Delmastro +1
The multitude of data generated by sensors available on users' mobile devices, combined with advances in machine learning techniques, support context-aware services in recognizing…
AVeCQ: Anonymous Verifiable Crowdsourcing with Worker Qualities
Sankarshan Damle, Vlasis Koutsos, Dimitrios Papadopoulos +2
In crowdsourcing systems, requesters publish tasks, and interested workers provide answers to get rewards. Worker anonymity motivates participation since it protects their privacy.…
Towards Mobile Distributed Ledgers
Dimitris Chatzopoulos, Anurag Jain, Sujit Gujar +2
Advances in mobile computing have paved the way for new types of distributed applications that can be executed solely by mobile devices on device-to-device (D2D) ecosystems (e.g.,…
IPLS : A Framework for Decentralized Federated Learning
Christodoulos Pappas, Dimitris Chatzopoulos, Spyros Lalis +1
The proliferation of resourceful mobile devices that store rich, multidimensional and privacy-sensitive user data motivate the design of federated learning (FL), a machine-learning…