Online learning of time-varying unbalanced networks in non-convex environments: A multi-armed bandit approach
OT Odeyomi - IEEE Access, 2023 - ieeexplore.ieee.org
This study discusses how agents in a time-varying distributed network can converge to the
global minimizer of a time-varying graph network. Each agent knows only the local loss of its …
global minimizer of a time-varying graph network. Each agent knows only the local loss of its …
Differential Privacy in Social Networks Using Multi-Armed Bandit
OT Odeyomi - IEEE Access, 2022 - ieeexplore.ieee.org
There has been an exponential growth over the years in the number of users connected to
social networks. This has spurred research interest in social networks to ensure the privacy …
social networks. This has spurred research interest in social networks to ensure the privacy …
Learning the truth by weakly connected agents in social networks using multi-armed bandit
OT Odeyomi - IEEE Access, 2020 - ieeexplore.ieee.org
This article provides a study into the social network where influential personalities
collaborate positively among themselves to learn an underlying truth over time, but may …
collaborate positively among themselves to learn an underlying truth over time, but may …