TP4a.4

Average Reward Reinforcement Learning for Wireless Radio Resource Management

Kun Yang, University of Virginia, United States; Jing Yang, The Pennsylvania State University, United States; Cong Shen, University of Virginia, United States
Session:
TP4a: Machine Learning for Communications II Lecture
Track:
Communication Systems
Location:
Nautilus
Presentation Time:
Tue, 29 Oct, 14:45 - 15:10 PT (UTC -8)
Session Co-Chairs:
Jeffrey Andrews, University of Texas at Austin and Nhan Nguyen, University of Oulu
Presentation
Discussion
Resources
No resources available.
Session TP4a
TP4a.1: AI-assisted link adaptation: Predicting hybrid automatic repeat request success
Emre Gonultas, Swathi Dhandhapani, Stefan Adalbjörnsson, Zaigham Kazmi, Ericsson Inc., United States
TP4a.2: Robust Antenna Parameter Optimization in Cellular Networks via Adversarial Machine Learning
Ezgi Tekgul, The University of Texas at Austin, United States; Salam Akoum, AT&T Labs, United States; Jeffrey Andrews, The University of Texas at Austin, United States
TP4a.3: A Bayesian Learning Approach to Wireless Outdoor Heatmap Construction using Deep Gaussian Process
Xiang Zhang, Yanyu Hu, University of Utah, United States; Imtiaz Nasim, Shannon Eggers, Vivek Agarwal, Amitabh Mishra, Joshua Daw, Arupjyoti Bhuyan, Idaho National Laboratory, United States; Sneha Kasera, Mingyue Ji, University of Utah, United States
TP4a.4: Average Reward Reinforcement Learning for Wireless Radio Resource Management
Kun Yang, University of Virginia, United States; Jing Yang, The Pennsylvania State University, United States; Cong Shen, University of Virginia, United States
Contacts