Q-Ising integrates Bayesian dynamic Ising modeling with offline RL to enable adaptive network treatment policies that outperform static centrality benchmarks under spillovers.
arXiv preprint arXiv:1503.00024 , year=
2 Pith papers cite this work. Polarity classification is still indexing.
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BARE is a bandit strategy for identifying the most influential node in an unknown graph, with regret scaling with the detectable dimension rather than the full number of nodes.
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Dynamic Treatment on Networks
Q-Ising integrates Bayesian dynamic Ising modeling with offline RL to enable adaptive network treatment policies that outperform static centrality benchmarks under spillovers.
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Revealing graph bandits for maximizing local influence
BARE is a bandit strategy for identifying the most influential node in an unknown graph, with regret scaling with the detectable dimension rather than the full number of nodes.