Extensions of Dynamic Programming, Machine Learning, Discrete Optimization Overview Main research areas: Extensions of Dynamic Programming (sequential optimization relative to different cost functions, counting of optimal solutions, construction of the set of Pareto optimal points, study of relationships between two cost functions) Machine Learning and Data Mining (multi-pruning of decision trees and knowledge representation both based on dynamic programming approach, relationships between exact learning and test theory, study of decision trees over infinite sets of attributes) Discrete Optimization (analysis and multi-criteria optimization of decision and inhibitory trees and rules, element partition trees for rectangular meshes, and objects in various combinatorial optimization problems) Applied Healthcare Analytics (simulation and optimization of organ allocation policies, analysis of kidney exchange problem) Published books: The following books were authored or co-authored by the TREES group members:
