Rethinking Trust Region Bayesian Optimization in High Dimensions
arXiv 2604.22967•6b654b1727de95d5dfa7e86f580e3df4d3ecd85e13955bf2caf315994f7cc207
TuRBOarXivbayesian-inversionbayesian-optimizationbenign-overfittingcausal-inferenceclusteringfermat-distanceflow-cytometrygaussian-processgraph-neural-networkshigh-dimensionalintegral-representationskernelsmachine-learningnesterov-accelerationone-way-attentiononline-newtonprobabilistic-graphical-modelssemi-supervised-learningsketchingspectral-methodstransformerstwo-layer-ReLUuncertainty-quantification
Paper metadata
- arXiv ID
- 2604.22967
- 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
- 6b654b1727de95d5dfa7e86f580e3df4d3ecd85e13955bf2caf315994f7cc207
- Enrichment time
- 2026-04-28T07:23:55Z
- AI-assisted enrichment
- Yes
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