Generalization error bounds for two-layer neural networks with Lipschitz loss function
arXiv 2604.06281•7ddec63e0794fe9f197c07656107d614b8e4d7931ee01a98bbfe7883763cd65f
adversarial-robustnesscode-availableconformal-predictiondifferential-privacydistributed-estimationfederated-learningfiltering-and-smoothinggaussian-processgeneralization-boundshigh-dimensional-statisticslabel-noise-robustnessmachine-learningmodel-poisoningnormalizing-flowsreinforcement-learningscalable-mlspiking-neural-networksstochastic-gradient-descenttheorywasserstein-distance
Paper metadata
- arXiv ID
- 2604.06281
- 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
- 7ddec63e0794fe9f197c07656107d614b8e4d7931ee01a98bbfe7883763cd65f
- Enrichment time
- 2026-04-09T07:24:04Z
- AI-assisted enrichment
- Yes
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