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 Statistical Learning

Bayesian decision-making under misspecified priors with applications to meta-learning Max Simchowitz Christopher Tosh

Neural Information Processing Systems

Our bound does not require the prior to have any parametric form.

Bayesian decision-making under misspecified priors with applications to meta-learning Max Simchowitz Christopher Tosh

Neural Information Processing Systems

Our bound does not require the prior to have any parametric form.

ddbc86dc4b2fbfd8a62e12096227e068-Supplemental.pdf

A Appendix

dda99de58ff020cfb57fec1404c97003-Paper.pdf

dcf531edc9b229acfe0f4b87e1e278dd-Paper.pdf

b2c4b7d34b3d96b9dc12f7bce424b7ae-Paper-Conference.pdf

Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders

Neural Information Processing Systems

The ability to answer causal questions is crucial in many domains, as causal inference allows one to understand the impact of interventions.

A Appendix Contents

Neural Information Processing Systems

Hyperparameters were lightly tuned by hand.

b24426d44bfbef35e24812c996752ceb-Paper-Conference.pdf