TP1a.3

Insights on f-Divergence-Based Surrogate Objective Functions for Mutual Information Maximization

Nicola Novello, Nunzio A. Letizia, University of Klagenfurt, Austria; Deniz Gündüz, Imperial College London, United Kingdom; Andrea M. Tonello, University of Klagenfurt, Austria
Session:
TP1a: Machine Learning for Communications Lecture
Track:
Communication Systems
Location:
Room 1
Presentation Time:
Tue, 27 Oct, 14:20 - 14:45 PT (UTC -7)
Session Chair:
Andrea Tonello, Universität Klagenfurt, Austria
Presentation
Discussion
Resources
No resources available.
Session TP1a
TP1a.1: Reducing Complexity of Graph Neural Network-based Message Passing Detection
Jannis Clausius, Stephan ten Brink, University of Stuttgart, Germany
TP1a.2: Site-Specific Finetuning of Wireless Receivers
Reinhard Wiesmayr, Nuri Berke Baytekin, ETH Zurich, Switzerland; Chris Dick, NVIDIA, United States; Christoph Studer, ETH Zurich, Switzerland
TP1a.3: Insights on f-Divergence-Based Surrogate Objective Functions for Mutual Information Maximization
Nicola Novello, Nunzio A. Letizia, University of Klagenfurt, Austria; Deniz Gündüz, Imperial College London, United Kingdom; Andrea M. Tonello, University of Klagenfurt, Austria
TP1a.4: AI-native Semantic Communications via Causal Information Bottleneck
Giuseppe Di Poce, CEA-LETI, France; Gabriele D'Acunto, Department of Information Engineering, Electronics, and Telecommunications, Sapienza University, Rome, Italy, Italy; Emilio Calvanese Strinati, CEA-LETI, France; Sergio Barbarossa, Paolo Di Lorenzo, Department of Information Engineering, Electronics, and Telecommunications, Sapienza University, Rome, Italy, Italy
Contacts