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Found 7 papers, 0 papers with code
Distributed Fractional Bayesian Learning for Adaptive Optimization
This paper considers a distributed adaptive optimization problem, where all agents only have access to their local cost functions with a common unknown parameter, whereas they mean to collaboratively estimate the true parameter and find the optimal solution over a connected network.
Data-driven Dynamic Event-triggered Control
This paper revisits the event-triggered control problem from a data-driven perspective, where unknown continuous-time linear systems subject to disturbances are taken into account.
A Novel Dynamic Event-triggered Mechanism for Dynamic Average Consensus
This paper studies a challenging issue introduced in a recent survey, namely designing a distributed event-based scheme to solve the dynamic average consensus (DAC) problem.
A Framework on Fully Distributed State Estimation and Cooperative Stabilization of LTI Plants
Further, the proposed method can be applied to pure fully distributed state estimation scenarios and modified for noise-bounded LTI plants.
Cooperative Control of Multi-Channel Linear Systems with Self-Organizing Private Agents
Cooperative behavior design for multi-agent systems with collective tasks is a critical issue in promoting swarm intelligence.
Data-Driven Deep Learning Based Hybrid Beamforming for Aerial Massive MIMO-OFDM Systems with Implicit CSI
To this end, by modeling the key transmission modules as an end-to-end (E2E) neural network, this paper proposes a data-driven deep learning (DL)-based unified hybrid beamforming framework for both the time division duplex (TDD) and frequency division duplex (FDD) systems with implicit channel state information (CSI).
Multi-Task Variational Information Bottleneck
Multi-task learning (MTL) is an important subject in machine learning and artificial intelligence.
