4 citations · 9 across the 12 of their papers we have counts for
6 papers · 1 filter
SheafAlign: A Sheaf-theoretic Framework for Decentralized Multimodal Alignment
Abdulmomen Ghalkha, Zhuojun Tian, Chaouki Ben Issaid +1
Conventional multimodal alignment methods assume mutual redundancy across all modalities, an assumption that fails in real-world distributed scenarios. We propose SheafAlign, a she…
Resilient-Native and Intelligent Next-Generation Wireless Systems: Key Enablers, Foundations, and Applications
Mehdi Bennis, Sumudu Samarakoon, Tamara Alshammari +3
Just like power, water, and transportation systems, wireless networks are a crucial societal infrastructure. As natural and human-induced disruptions continue to grow, wireless net…
Sheaf-Based Decentralized Multimodal Learning for Next-Generation Wireless Communication Systems
Abdulmomen Ghalkha, Zhuojun Tian, Chaouki Ben Issaid +1
In large-scale communication systems, increasingly complex scenarios require more intelligent collaboration among edge devices collecting various multimodal sensory data to achieve…
Learning to Collaborate Over Graphs: A Selective Federated Multi-Task Learning Approach
Ahmed Elbakary, Chaouki Ben Issaid, Mehdi Bennis
We present a novel federated multi-task learning method that leverages cross-client similarity to enable personalized learning for each client. To avoid transmitting the entire mod…
Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences
Adnan Shahid, Adrian Kliks, Ahmed Al-Tahmeesschi +132
This white paper discusses the role of large-scale AI in the telecommunications industry, with a specific focus on the potential of generative AI to revolutionize network functions…
Tackling Feature and Sample Heterogeneity in Decentralized Multi-Task Learning: A Sheaf-Theoretic Approach
Chaouki Ben Issaid, Praneeth Vepakomma, Mehdi Bennis
Federated multi-task learning (FMTL) aims to simultaneously learn multiple related tasks across clients without sharing sensitive raw data. However, in the decentralized setting, e…