3 accepted papers
Large language models (LLMs) are trained using massive datasets.However, these datasets often contain undesirable content, e.g., harmful texts, personal information, and copyrighted material.To address this, machine unlearning aims to remove information from trained models.Recent work has shown that
In every communication round of federated learning, a random subset of clients communicate their model updates back to the server which then aggregates them all. The optimal size of this subset is not known and several studies have shown that typically random selection does not perform ve…
We consider the problem of allocating radio resources over wireless communication links to control a series of independent low-latency wireless control systems common in industrial settings. Supporting wireless control in time sensitive settings requires fast data rates over wireless links, which co…