Adaptive Learning via Off-Model Training and Importance Sampling for Fully Non-Markovian Optimal Stochastic Control. Complete version
arXiv 2604.13147•b24d4bb655164a9c6bc1950357835a32a283064e7c77c624eef42dbc9c7235f1
ADMMGaussian mixture modelsLangevin dynamicsM-productcausal representation learningclusteringcommittorconditional diffusionconformal inferencecovariance estimationimportance samplingkernel ridge regressionlow-rank tensor completionmachine learningmanifold optimizationmeta-learningnon-Markovian processesoptimizationrare-event samplingsemi-banditsstochastic controlt-SNE limitationstime-series forecastingtransition path theory
Paper metadata
- arXiv ID
- 2604.13147
- Version
- Not specified by this published record
- Category
- Statistics — Machine Learning (stat.ML)
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- Source ID
- arxiv_stat_ml
- Record identifier
- b24d4bb655164a9c6bc1950357835a32a283064e7c77c624eef42dbc9c7235f1
- Enrichment time
- 2026-04-16T07:23:59Z
- AI-assisted enrichment
- Yes
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