TP4a: Machine Learning for Communications
Tue, 29 Oct, 13:30 - 15:10 PT (UTC -7)
Location: Nautilus
Session Type: Lecture
Track: Communication Systems
Tue, 29 Oct, 13:30 - 13:55 PT (UTC -7)

TP4a.1: AI-assisted link adaptation: Predicting hybrid automatic repeat request success
Emre Gonultas, Swathi Dhandhapani, Stefan Adalbjörnsson, Zaigham Kazmi, Ericsson Inc., United States
Tue, 29 Oct, 13:55 - 14:20 PT (UTC -7)

TP4a.2: 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
Tue, 29 Oct, 14:20 - 14:45 PT (UTC -7)

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
Tue, 29 Oct, 14:45 - 15:10 PT (UTC -7)

TP4a.4: 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