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A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,878 papers · 148 categories

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1 result for “Meta-Sub-Targets”
Blending-target Domain Adaptation by Adversarial Meta-Adaptation Networkscs.LG

AMEAN tackles BTDA by learning meta-sub-targets to bridge domain gaps and misalignments.

problem Blending-target Domain Adaptation (BTDA) with multiple sub-targets that are hard to distinguish.
method AMEAN uses two adversarial processes: first to align source and mixed target domains, second to learn meta-sub-targets.
result AMEAN significantly outperforms existing DA algorithms in BTDA scenarios.
Domain AdaptationMeta-LearningAdversarial NetworksMeta-Sub-TargetsBlending-Target
2019-07-08abs ↗pdf ↗