2 papers
cs.IT2024
Cell-Free Multi-User MIMO Equalization via In-Context Learning
Matteo Zecchin, Kai Yu, Osvaldo Simeone
Large pre-trained sequence models, such as transformers, excel as few-shot learners capable of in-context learning (ICL). In ICL, a model is trained to adapt its operation to a new…
cs.IT2023
In-Context Learning for MIMO Equalization Using Transformer-Based Sequence Models
Matteo Zecchin, Kai Yu, Osvaldo Simeone
Large pre-trained sequence models, such as transformer-based architectures, have been recently shown to have the capacity to carry out in-context learning (ICL). In ICL, a decision…