Unverified50% confidenceFactExact time
The paper uses a tensor criterion to classify distribution families into three regimes: everywhere optimal (R=1), dimension-independent bounded overhead, and Θ(√log d) divergence with dimensionality.
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10/7/2026
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UnverifiedThe posterior distribution is obtained via Bayes' theorem: p(θ|x) ∝ p(x|θ)·p(θ), combining prior knowledge with the data likelihood.72% similarUnverifiedThe three technical approaches each have their own emphasis: conditional quantile regression is relatively straightforward to implement, quantile function estimation provides more complete distributional information, and the localization method is more targeted in addressing non-stationarity.72% similarUnverifiedThe robustness of a distribution essentially depends on how its tail behavior is modeled, and replacing the Gaussian distribution with a heavy-tailed distribution can improve a model's stability against outliers.66% similarUnverifiedIn the Bayesian framework, the prior plays the role of regularization, and adding a regularization term is essentially equivalent to introducing a certain prior distribution for the parameters.64% similarUnverifiedOU过程的平稳分布为高斯分布，其转移核为高斯分布，使任意时刻的条件分布可以精确计算63% similar
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