Spectral bandits achieve scalable regret in graph-structured recommendation by using an effective dimension to learn good policies from few node evaluations.
On the likelihood that one unknown probability exceeds another in view of the evidence of two samples
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
The thesis compiles work on graph bandits (spectral smoothness, side observations, influence maximization) and structured bandits (kernel, polymatroid, function optimization with unknown smoothness, infinite arms) to improve practicality.
citing papers explorer
-
Spectral bandits
Spectral bandits achieve scalable regret in graph-structured recommendation by using an effective dimension to learn good policies from few node evaluations.
-
Bandits on graphs and structures
The thesis compiles work on graph bandits (spectral smoothness, side observations, influence maximization) and structured bandits (kernel, polymatroid, function optimization with unknown smoothness, infinite arms) to improve practicality.