d^{poly(ℓ/ε)} algorithms for exponential families under polynomial-approximable unknown truncation, including first results for arbitrary Gaussians; poly(d/ε) for halfspaces/rectangles.
Imbens and Donald B
8 Pith papers cite this work. Polarity classification is still indexing.
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CausaLab introduces a scalable benchmark for LLM agents on interactive causal discovery using random SCMs, revealing high task accuracy but low structural recovery in experiments with models like GPT-5.2.
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Biomass burning aerosols produce -2.5 W m^{-2} regional shortwave cooling over the South-East Atlantic, decomposed equally into ARI, ARI adjustments, and ACI after causal removal of confounding biases.
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Hierarchical clustering of geos by marketing spend correlation after normalization reduces multicollinearity and enables separate causal identification of ad channel effects in a Bayesian marketing mix model.
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Efficient Statistics With Unknown Truncation, Polynomial Time Algorithms, Beyond Gaussians
d^{poly(ℓ/ε)} algorithms for exponential families under polynomial-approximable unknown truncation, including first results for arbitrary Gaussians; poly(d/ε) for halfspaces/rectangles.