2022/09/11 by Zhang, Jinxiong
#Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Numerical Analysis (math.NA)
paper · doi:10.48550/arxiv.2209.04825
This paper introduces a series of methods for traversing binary decision trees using arithmetic operations. We present a suite of binary tree traversal algorithms that leverage novel representation matrices to flatten the full binary tree structure and embed the aggregated internal node Boolean tests into a single binary vector. Our approach, grounded in maximum inner product search, offers new insights into decision tree.