[2408.09537] Sample|Optimal Large|Scale Optimal Subset Selection
[2408.09537] Sample-Optimal Large-Scale Optimal Subset Selection
We design a top-m greedy selection mechanism that keeps sampling the current top m alternatives with top m running sample means and propose the explore-first ...
Sample-Optimal Large-Scale Optimal Subset Selection - arXiv
arXiv:2408.09537v1 [stat.ML] 18 Aug 2024. Page 2. 2 and selection (R&S) and has been widely studied in simulation community. When the sampling.
[2408.09537] Sample-Optimal Large-Scale Optimal Subset Selection
arXiv:2408.09537 (stat). [Submitted on 18 Aug 2024]. Title:Sample-Optimal Large-Scale Optimal Subset Selection. Authors:Zaile Li, Weiwei Fan, L. Jeff Hong. View ...
Sample-Optimal Large-Scale Optimal Subset Selection - AIModels.fyi
Sample-Optimal Large-Scale Optimal Subset Selection. Read original: arXiv:2408.09537 - Published 8/19/2024 by Zaile Li, Weiwei Fan, L. Jeff Hong.
Weiwei Fan - Google Scholar
Sample-Optimal Large-Scale Optimal Subset Selection. Z Li, W Fan, LJ Hong. arXiv preprint arXiv:2408.09537, 2024. 2024. A Deep Q-Network Based on Radial Basis ...
Statistics Papers on X: "Sample-Optimal Large-Scale Optimal ...
Sample-Optimal Large-Scale Optimal Subset Selection. https://t.co/phjDhb5Dhg.
Weiwei Fan - Google Scholar
Sample-Optimal Large-Scale Optimal Subset Selection. Z Li, W Fan, LJ Hong. arXiv preprint arXiv:2408.09537, 2024. 2024. A Deep Q-Network Based on Radial Basis ...
Weiwei Fan - الباحث العلمي من Google
Sample-Optimal Large-Scale Optimal Subset Selection. Z Li, W Fan, LJ Hong. arXiv preprint arXiv:2408.09537, 2024. 2024. A Deep Q-Network Based on Radial ...
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arXiv:2408.09537 [pdf, other]. stat.ML cs.LG stat.ME. Sample-Optimal Large-Scale Optimal Subset Selection. Authors: Zaile Li, Weiwei Fan, L. Jeff Hong. Abstract ...
Sample-Optimal Large-Scale Optimal Subset Selection. CoRR abs/2408.09537 (2024) ... Indifference-Zone-Free Selection of the Best ... perfect. [+][–]. Coauthor Index.
Best-Subset Selection Criteria for Multiple Linear Regression
... large number of coefficient and multicollinearity patterns, AIC and adjusted R2 work reasonably well enough to recommend, in combination, to identify a ...
Lab 8 - Subset Selection in R - Smith College
The regsubsets() function (part of the leaps library) performs best subset selection by identifying the best model that contains a given number of predictors.
Model Performance Following Best Subset Selection
I was just curious to whether performance measures like R^2, Brier score, calibration slope/intercept etc. are as applicable on Best Subset Selection (BSS)/ ...