arXiv Machine Learning July 27, 2026 By Yigit Berkay Uslu, Navid NaderiAlizadeh, Mark Eisen, Alejandro Ribeiro

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression

Read the original on arXiv Machine Learning →

arXiv:2506. 18748v2 Announce Type: replace-cross Abstract: We consider resource allocation problems in multi-user wireless networks, where the goal is to optimize a network-wide utility function subject to constraints on the ergodic average performance of users.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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