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of 44
pro vyhledávání: '"Shin, Jaehyeok"'
Sequential change detection is a classical problem with a variety of applications. However, the majority of prior work has been parametric, for example, focusing on exponential families. We develop a fundamentally new and general framework for sequen
Externí odkaz:
http://arxiv.org/abs/2203.03532
Autor:
Shin, Jaehyeok, Noh, Siyun, Lee, Jinseong, Jhee, Seunghwan, Choi, Ilgyu, Kyu Jeong, Chang, Heon Kim, Seong, Kim, Jin Soo
Publikováno v:
In Chemical Engineering Journal 15 April 2024 486
We develop a nonparametric extension of the sequential generalized likelihood ratio (GLR) test and corresponding time-uniform confidence sequences for the mean of a univariate distribution. By utilizing a geometric interpretation of the GLR statistic
Externí odkaz:
http://arxiv.org/abs/2010.08082
The bias of the sample means of the arms in multi-armed bandits is an important issue in adaptive data analysis that has recently received considerable attention in the literature. Existing results relate in precise ways the sign and magnitude of the
Externí odkaz:
http://arxiv.org/abs/2002.08422
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Akademický článek
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It is well known that in stochastic multi-armed bandits (MAB), the sample mean of an arm is typically not an unbiased estimator of its true mean. In this paper, we decouple three different sources of this selection bias: adaptive \emph{sampling} of a
Externí odkaz:
http://arxiv.org/abs/1905.11397
We show how to convert any clustering into a prediction set. This has the effect of converting the clustering into a (possibly overlapping) union of spheres or ellipsoids. The tuning parameters can be chosen to minimize the size of the prediction set
Externí odkaz:
http://arxiv.org/abs/1903.08125
We derive conditions under which the reconstruction of a target space is topologically correct via the \v{C}ech complex or the Vietoris-Rips complex obtained from possibly noisy point cloud data. We provide two novel theoretical results. First, we de
Externí odkaz:
http://arxiv.org/abs/1903.06955
The sample mean is among the most well studied estimators in statistics, having many desirable properties such as unbiasedness and consistency. However, when analyzing data collected using a multi-armed bandit (MAB) experiment, the sample mean is bia
Externí odkaz:
http://arxiv.org/abs/1902.00746