23 citations · 58 across the 52 of their papers we have counts for
6 papers · 2 filters
Contribution-Aware Bandwidth Allocation for Multimodal Split Learning
Iason Ofeidis, Leandros Tassiulas
Multimodal models are increasingly the default option for perception at the network edge, yet they are trained almost entirely in the datacenter, because a client holding several s…
Reasoning through Verifiable Forecast Actions: Consistency-Grounded RL for Financial LLMs
Jialin Chen, Aosong Feng, Harshit Verma +7
Financial markets are characterized by extreme non-stationarity, low signal-to-noise ratios, and strong dependence on external information such as news, company fundamentals, and m…
Rank Is Not Capacity: Spectral Occupancy for Latent Graph Models
Nikolaos Nakis, Panagiotis Promponas, Konstantinos Tsirkas +4
Graph representation learning has become a standard approach for analyzing networked data, with latent embeddings widely used for link prediction, community detection, and related…
CLAD: A Clustered Label-Agnostic Federated Learning Framework for Joint Anomaly Detection and Attack Classification
Iason Ofeidis, Nikos Papadis, Randeep Bhatia +2
The rapid expansion of the Internet of Things (IoT) and Industrial IoT (IIoT) has created a massive, heterogeneous attack surface that challenges traditional network security mecha…
Hierarchical Federated Learning for Networked AI: From Communication Saving to Architecture-Aware Design
Seyed Mohammad Azimi-Abarghouyi, Mehdi Bennis, Leandros Tassiulas
Federated learning (FL) is fundamentally a distributed optimization problem executed by communicating agents with local data, local computation, and partial system visibility. Once…
Multi-Modal Time Series Prediction via Mixture of Modulated Experts
Lige Zhang, Ali Maatouk, Jialin Chen +3
Real-world time series exhibit complex and evolving dynamics, making accurate forecasting extremely challenging. Recent multi-modal forecasting methods leverage textual information…