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Beskrivning
In this book, we introduce different types of biological data missing scenarios and propose machine learning models to improve the data analysis, including deep recurrent neural network recovery for feature missings, robust information theoretic learning for label missings and structure-aware rebalancing for minor sample missings.
Feng Bao currently is a Postdoctoral Scholar at University of California, San Francisco. He received the Ph.D. degree in control science and engineering from Department of Automation, Tsinghua University, Beijing, China, in 2019. His research interest covers machine learning, computational biology, cell profiling technologies.
Innehållsförteckning
Chapter 1 Introduction.- Chapter 2 Fast computational recovery of missing features for large-scale biological data.- Chapter 3 Computational recovery of information from low-quality and missing labels.- Chapter 4 Computational recovery of sample missings.- Chapter 5 Summary and outlook.