4 papers
Efficient Analytic Uncertainty Quantification for Multi-Modal Regression
Kun Jin, James Harrison, Jiawei Li +8
Efficient uncertainty quantification (UQ) is essential for trustworthy large-scale learning. Existing UQ methods for regression tasks mainly operate under the assumption that the c…
From Generative to Episodic: Sample-Efficient Replicable Reinforcement Learning
Max Hopkins, Sihan Liu, Christopher Ye +1
The epidemic failure of replicability across empirical science and machine learning has recently motivated the formal study of replicable learning algorithms [Impagliazzo et al. (2…
Replicable Distribution Testing
Ilias Diakonikolas, Jingyi Gao, Daniel Kane +2
We initiate a systematic investigation of distribution testing in the framework of algorithmic replicability. Specifically, given independent samples from a collection of probabili…
Replicable Uniformity Testing
Sihan Liu, Christopher Ye
Uniformity testing is arguably one of the most fundamental distribution testing problems. Given sample access to an unknown distribution on , one must decide if $…