Moment-based method identifies regression coefficient beta and LDA concentration alpha_0 from response-weighted corrected word moments and commutativity, without per-document topic estimation.
Inference for regression with variables generated by ai or machine learning.arXiv preprint arXiv:2402.15585
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UNVERDICTED 4representative citing papers
A coupled-label bootstrap provides valid inference for OLS regressions that use AI/ML-generated binary labels despite misclassification errors, unlike standard fixed-label bootstraps.
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A new framework combines AI-derived concept embeddings with high-dimensional selective inference to enable statistically principled, interpretable discovery from unstructured data in empirical economics.
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Moment-Based Inference for Regression with Latent Dirichlet Covariates
Moment-based method identifies regression coefficient beta and LDA concentration alpha_0 from response-weighted corrected word moments and commutativity, without per-document topic estimation.
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Bootstrapping with AI/ML-generated labels
A coupled-label bootstrap provides valid inference for OLS regressions that use AI/ML-generated binary labels despite misclassification errors, unlike standard fixed-label bootstraps.
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A Deep Learning Approach to Heterogeneous Consumer Aesthetics in Fast Fashion
A three-tower embedding model fine-tuned from Fashion CLIP combined with a latent-class deep demand system captures heterogeneous consumer aesthetics, price sensitivities, and substitution patterns from large-scale retail transaction data.
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A new framework combines AI-derived concept embeddings with high-dimensional selective inference to enable statistically principled, interpretable discovery from unstructured data in empirical economics.