2 citations · 3 across the 15 of their papers we have counts for
4 papers · 1 filter
Efficient Semantic Communication Through Transformer-Aided Compression
Matin Mortaheb, Mohammad A. Amir Khojastepour, Sennur Ulukus
Transformers, known for their attention mechanisms, have proven highly effective in focusing on critical elements within complex data. This feature can effectively be used to addre…
Age-: Communication-Efficient Federated Learning Using Age Factor
Matin Mortaheb, Priyanka Kaswan, Sennur Ulukus
Federated learning (FL) is a collaborative approach where multiple clients, coordinated by a parameter server (PS), train a unified machine-learning model. The approach, however, s…
Age of Gossip in Networks with Multiple Views of a Source
Kian J. Khojastepour, Matin Mortaheb, Sennur Ulukus
We consider the version age of information (AoI) in a network where a subset of nodes act as sensing nodes, sampling a source that in general can follow a continuous distribution.…
Transformer-Aided Semantic Communications
Matin Mortaheb, Erciyes Karakaya, Mohammad A. Amir Khojastepour +1
The transformer structure employed in large language models (LLMs), as a specialized category of deep neural networks (DNNs) featuring attention mechanisms, stands out for their ab…