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Found 3 papers, 1 papers with code
Semantic Communication of Learnable Concepts
The transmitter applies a learning algorithm to the available examples, and extracts knowledge from the data by optimizing a probability distribution over a set of models, i. e., known functions, which can better describe the observed data, and so potentially the underlying concepts.
Federated mmWave Beam Selection Utilizing LIDAR Data
Efficient link configuration in millimeter wave (mmWave) communication systems is a crucial yet challenging task due to the overhead imposed by beam selection.
Effective Communications: A Joint Learning and Communication Framework for Multi-Agent Reinforcement Learning over Noisy Channels
Specifically, we consider a multi-agent partially observable Markov decision process (MA-POMDP), in which the agents, in addition to interacting with the environment can also communicate with each other over a noisy communication channel.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
