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Merging versus Ensembling in Multi-Study Machine Learning: Theoretical Insight from Random Effects., , and . CoRR, (2019)Mining personalized medicine algorithms with surrogate algorithm tags., , , , , and . IHI, page 474-478. ACM, (2010)Cloud computing for comparative genomics., , , , , and . BMC Bioinform., (2010)Multi-Study Boosting: Theoretical Considerations for Merging vs. Ensembling., , , and . CoRR, (2022)Towards More Universal Wayfinding Technologies: Navigation Preferences Across Disabilities., , , , , , , , , and 1 other author(s). CHI, page 1-13. ACM, (2020)Robustifying genomic classifiers to batch effects via ensemble learning., , , and . Bioinform., 37 (11): 1521-1527 (2021)Test set bias affects reproducibility of gene signatures., , , and . Bioinform., 31 (14): 2318-2323 (2015)Discussion of "visualizing statistical models: Removing the blindfold"., and . Stat. Anal. Data Min., 8 (4): 240-241 (2015)Tree-Weighting for Multi-Study Ensemble Learners., , and . PSB, page 451-462. (2020)A pairwise strategy for imputing predictive features when combining multiple datasets., , and . Bioinform., (January 2023)