Tag: bayes
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Universal priors: solving empirical Bayes via Bayesian inference and pretraining
Universal priors: solving empirical Bayes via Bayesian inference and pretraining arXiv:2602.15136v1 Announce Type: new Abstract: We theoretically justify the recent empirical finding of [Teh et al., 2025] that a transformer pretrained on synthetically generated data achieves strong performance on empirical Bayes (EB) problems. We take an indirect approach to this question: rather than analyzing the…
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Bayes and Biased Estimators Without Hyper-parameter Estimation: Comparable Performance to the Empirical-Bayes-Based Regularized Estimator
Bayes and Biased Estimators Without Hyper-parameter Estimation: Comparable Performance to the Empirical-Bayes-Based Regularized Estimator arXiv:2503.11854v1 Announce Type: new Abstract: Regularized system identification has become a significant complement to more classical system identification. It has been numerically shown that kernel-based regularized estimators often perform better than the maximum likelihood estimator in terms of minimizing mean squared…
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Bayes’ Theorem: Understanding business outcomes with evidence
Bayes’ Theorem: Understanding business outcomes with evidence A practical introduction to Bayes’ Theorem: Probability for Data Science Series (2) Continue reading on Towards Data Science » Sunghyun Ahn Go to original source