TA5a.2

Dynamic Adaptive Inference with Reinforcement Learning in Time-Varying Future Generation Sensing Environments

Abigail Eastman, Yongho Seo, Antonia Papandreou-Suppappola, Arizona State University, United States
Session:
TA5a: Integrated Learning and Processing for Future Generation Wireless Sensing Lecture
Track:
Array Processing and Multisensor Systems
Location:
Toyon
Presentation Time:
Tue, 28 Oct, 08:40 - 09:05 PT (UTC -7)
Presentation
Discussion
Resources
No resources available.
Session TA5a
TA5a.1: Low-cost and Scalable Zone-specific CSI Feedback for FutureG Networks
Yan Xiong, Chaitali Chakrabarti, Ahmed Alkhateeb, Arizona State University, United States
TA5a.2: Dynamic Adaptive Inference with Reinforcement Learning in Time-Varying Future Generation Sensing Environments
Abigail Eastman, Yongho Seo, Antonia Papandreou-Suppappola, Arizona State University, United States
TA5a.3: Demonstration of Enabling Computational Technologies for RF Convergence
Saquib Siddiqui, Alex Chiriyath, Andrew Herschfelt, Daniel Bliss, Arizona State University, United States
TA5a.4: Reconfigurable System Design and Trade Studies for Dynamic Spectral Sensing
Arindam Dutta, Arizona State University, United States; Jiahao Lin, University of Wisconsin-Madison, United States; H. Umut Suluhan, University of Arizona, United States; Gerard Gubash, Arizona State University, United States; Ali Akoglu, University of Arizona, United States; Umit Y. Ogras, University of Wisconsin-Madison, United States; Bernd-Peter Paris, George Mason University, United States
Contacts