Minimax PAC Bounds for Learning in Exogenous Contextual MDPs
arXiv 2606.25170•3dfb7d7750f4eb27fd93142c05d7b6ed8a88d4faa8109fa9d4cee6cd87cea57e
PAC-boundsPolyak-RuppertTD-learningblack-box-stabilityclass-imbalancecontextual-MDPdata-augmentationdiffusion-modelse-valuesfederated-learninghyperparameter-selectioninformation-theory','pac-bayes','ranking','partial-order-modelslarge-language-modelslearn-then-testmachine-learningmean-fieldp-valuesrandomizationreinforcement-learningsample-complexitystatisticssynthetic-augmentationtemporal-point-processesvariance-reductionvariational-inference
Paper metadata
- arXiv ID
- 2606.25170
- Version
- Not specified by this published record
- Category
- Statistics — Machine Learning (stat.ML)
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Evidence and limitations
- Source ID
- arxiv_stat_ml
- Record identifier
- 3dfb7d7750f4eb27fd93142c05d7b6ed8a88d4faa8109fa9d4cee6cd87cea57e
- Enrichment time
- 2026-06-25T07:23:56Z
- AI-assisted enrichment
- Yes
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