Empirical Processes and Statistical Reinforcement Learning

Michael R. Kosorok has made significant contributions to biostatistics, precision medicine, machine learning and artificial intelligence, shaping the future of statistical methodology and biomedical research. Empirical Processes and Statistical Reinforcement Learning: A Festschrift in Honor of Michael R. Kosorok centres around his remarkable achievements.

The book encompasses topics such as empirical processes, semiparametric inference, causal inference, reinforcement learning, artificial intelligence, and precision medicine. With contributions from leading experts in the field, it highlights Michael R. Kosorok’s pivotal role in advancing statistical methodology for cancer research and treatment regimes.

This Festschrift serves both as a reference for researchers and a resource for PhD-level education in biostatistics and biomedical research.

Key Features:

• Informs the frontiers of methodological developments and their biomedical applications.
• Explains empirical processes and semiparametric inference, including minimax optimality and target localization in distributed systems.
• Provides in-depth insights into causal inference and reinforcement learning with topics like fair representation learning, synthetic control models, and causal reinforcement learning with unmeasured confounders.
• Showcases advancements in precision medicine, including individualized treatment rules, outcome-weighted learning, and applications in sports analytics.
• Includes contributions on statistical and machine learning methods for clinical decision-making and early detection.

Shuangge (Steven) Ma is a Professor of Biostatistics at the Yale School of Public Health. He was a Ph.D. student of Prof. Kosorok at the University of Wisconsin and worked with him on semiparametric modeling, survival analysis, and empirical processes.

Eric B. Laber is the James B. Duke Distinguished Professor of Statistical Sciences and Biostatistics and Bioinformatics at Duke University. He is a fellow of the American Statistical Association and International Statistical Institute as well as the recipient of the Gottfried E. Noether Award, the Raymond J. Carroll Award, and the American Statistical Association Outstanding Application Award.