ORID XrKzHGg2jB · tags icml2026-repro paper-XrKzHGg2jB
| # | Status | Page | Artifact | Claim excerpt |
|---|---|---|---|---|
| 1 | VERIFIED 2/2 | 01-stackelberg-littlestone-dimension-characterizes | artifact | The Stackelberg-Littlestone (SL) dimension characterizes the optimal mistake bou… |
| 2 | VERIFIED 2/2 | 02-algorithm-stackelberg-standard-optimal-algorithm | artifact | Algorithm 1 (the Stackelberg Standard Optimal Algorithm) achieves a regret bound… |
| 3 | VERIFIED 2/2 | 03-there-exist-stackelberg-game-instances | artifact | There exist Stackelberg game instances where the standard Littlestone dimension … |
| 4 | VERIFIED 2/2 | 04-agnostic-online-setting-algorithm-regret | artifact | In the agnostic online setting, the paper's algorithm achieves a regret bound of… |
| 5 | VERIFIED 2/2 | 05-distributional-learning-contexts-stackelberg-nat | artifact | For distributional learning with contexts, the Stackelberg-Natarajan (SN) dimens… |