Research map / Bandits and online learning / Multi-armed bandits
Combinatorial semi-bandit with known covariance
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Increase the maximal off-diagonal correlation gamma of arm noise (more correlated arms within an action) | OLS-UCB regret on parallel paths problem · Parallel paths problem, 5 paths | regret | Hurt |
| Use OLS-based UCB with subgaussian covariance-aware confidence (adapting to arm independence) instead of worst-case CombUCB1 exploration term | combinatorial semi-bandit regret · independent arms | regret upper bound order: O(d sqrt(m) log T / Delta) (ESCB-2) tightened to O(d log^2 m log T / Delta) | Helped |
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