AIS: Adaptive Importance Sampling for Quantized RL
arXiv 2605.13907•304536c98b5585e30a9967d1725a61dbd17f1f359b9587ad0788b4d878ebd339
BF16Bayesian-inferenceDDIMFP8INT8LLM-inferenceMXFP4Multi-Scale-Dequantabstentionchain-of-thoughtconformal-predictioncovariancedequantizationdiffusion-modelsfairnesshardware-accelerationimportance-samplingmachine-learningmean-shiftonline-multiple-testingparticle-systems','training-free-sampling','MM-SOLD','kernel-ridquantizationregretreinforcement-learningsamplers
Paper metadata
- arXiv ID
- 2605.13907
- 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
- 304536c98b5585e30a9967d1725a61dbd17f1f359b9587ad0788b4d878ebd339
- Enrichment time
- 2026-05-15T07:24:00Z
- AI-assisted enrichment
- Yes
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