199 citations · 208 across the 10 of their papers we have counts for
5 papers · 1 filter
Bayesian Learning for Dynamic Inference
Aolin Xu, Peng Guan
The traditional statistical inference is static, in the sense that the estimate of the quantity of interest does not affect the future evolution of the quantity. In some sequential…
Dynamic Inference
Aolin Xu
Traditional statistical estimation, or statistical inference in general, is static, in the sense that the estimate of the quantity of interest does not change the future evolution…
Continuity of Generalized Entropy and Statistical Learning
Aolin Xu
We study the continuity property of the generalized entropy as a function of the underlying probability distribution, defined with an action space and a loss function, and use this…
Minimum Excess Risk in Bayesian Learning
Aolin Xu, Maxim Raginsky
We analyze the best achievable performance of Bayesian learning under generative models by defining and upper-bounding the minimum excess risk (MER): the gap between the minimum ex…
Information-theoretic analysis of generalization capability of learning algorithms
Aolin Xu, Maxim Raginsky
We derive upper bounds on the generalization error of a learning algorithm in terms of the mutual information between its input and output. The bounds provide an information-theore…