Tag: theta
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Amortized Simulation-Based Inference in Generalized Bayes via Neural Posterior Estimation
Amortized Simulation-Based Inference in Generalized Bayes via Neural Posterior Estimation arXiv:2601.22367v1 Announce Type: new Abstract: Generalized Bayesian Inference (GBI) tempers a loss with a temperature $beta>0$ to mitigate overconfidence and improve robustness under model misspecification, but existing GBI methods typically rely on costly MCMC or SDE-based samplers and must be re-run for each new dataset…
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Tractable Instances of Bilinear Maximization: Implementing LinUCB on Ellipsoids
Tractable Instances of Bilinear Maximization: Implementing LinUCB on Ellipsoids arXiv:2511.07504v1 Announce Type: new Abstract: We consider the maximization of $x^top theta$ over $(x,theta) in mathcal{X} times Theta$, with $mathcal{X} subset mathbb{R}^d$ convex and $Theta subset mathbb{R}^d$ an ellipsoid. This problem is fundamental in linear bandits, as the learner must solve it at every time step…
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CoLT: The conditional localization test for assessing the accuracy of neural posterior estimates
CoLT: The conditional localization test for assessing the accuracy of neural posterior estimates arXiv:2507.17030v1 Announce Type: new Abstract: We consider the problem of validating whether a neural posterior estimate ( q(theta mid x) ) is an accurate approximation to the true, unknown true posterior ( p(theta mid x) ). Existing methods for evaluating the quality…
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PAC Learning with Improvements
PAC Learning with Improvements arXiv:2503.03184v1 Announce Type: new Abstract: One of the most basic lower bounds in machine learning is that in nearly any nontrivial setting, it takes $textit{at least}$ $1/epsilon$ samples to learn to error $epsilon$ (and more, if the classifier being learned is complex). However, suppose that data points are agents who have…