The Partition Principle Revisited: Non-Equal Volume Designs Achieve Minimal Expected Star Discrepancy
arXiv 2603.00202•ae36988bbc8f71bf1f668e58e92a4bca390a328bcd0fa2726fa4b02d27fb9bfb
LLM-evaluationbayesian-optimizationcausal-inferenceconformal-predictionconfounder-modelinggenerative-modelshuman-AI-systemslatent-space-optimizationmachine-learningmodel-robustnessneural-operatorsprivacy-implicationsrandom-featuresreliability-scoringrisk-aware-predictionsampling-efficiencyscore-based-diffusionspatio-temporal-analysisspectral-embeddingstime-varying-driftuncertainty-quantification
Paper metadata
- arXiv ID
- 2603.00202
- Version
- Not specified by this published record
- Category
- Statistics — Machine Learning (stat.ML)
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- Source ID
- arxiv_stat_ml
- Record identifier
- ae36988bbc8f71bf1f668e58e92a4bca390a328bcd0fa2726fa4b02d27fb9bfb
- Enrichment time
- 2026-03-04T20:01:04Z
- AI-assisted enrichment
- Yes
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