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Machine learning methods for improving drug response prediction in cancer.

. Aalto University, Espoo, Finland, (2017)base-search.net (ftaaltouniv:oai:aaltodoc.aalto.fi:123456789/27290).

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Drug response prediction by inferring pathway-response associations with kernelized Bayesian matrix factorization., , , , , , and . Bioinform., 32 (17): 455-463 (2016)GFA: Exploratory Analysis of Multiple Data Sources with Group Factor Analysis., , and . CoRR, (2016)GFA: Exploratory Analysis of Multiple Data Sources with Group Factor Analysis., , and . J. Mach. Learn. Res., (2017)Integrative and Personalized QSAR Analysis in Cancer by Kernelized Bayesian Matrix Factorization., , , , , , , and . J. Chem. Inf. Model., 54 (8): 2347-2359 (2014)Regression with n$\to$1 by Expert Knowledge Elicitation., , and . CoRR, (2016)Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System., , , , , , and . CoRR, (2019)Federated Multi-view Matrix Factorization for Personalized Recommendations., , , , , and . ECML/PKDD (2), volume 12458 of Lecture Notes in Computer Science, page 324-347. Springer, (2020)Regression with n→1 by Expert Knowledge Elicitation., , and . ICMLA, page 734-739. IEEE Computer Society, (2016)Systematic identification of feature combinations for predicting drug response with Bayesian multi-view multi-task linear regression., , , and . Bioinform., 33 (14): i359-i368 (2017)Machine learning methods for improving drug response prediction in cancer.. Aalto University, Espoo, Finland, (2017)base-search.net (ftaaltouniv:oai:aaltodoc.aalto.fi:123456789/27290).