Binary Space Partitioning as Intrinsic Reward

Which Space Partitioning Tree to Use for Search - Summary

Trees like binary-space-partitioning trees, kd-trees, principal axis trees and random projection trees are used to answer the question ”which tree to use for nearest-neighbor search?.” This paper deals with the influence of the vector quantization performance of the trees on the search performance and the margins of the partitions in these trees. Theoretical results show that both factors have ...

A Tutorial on Binary Space Partitioning Trees

Reinforcement Learning Trees

Two new reinforcement learning algorithms are presented. Both use a binary tree to store simple local models in the leaf nodes and coarser global models towards the root. It is demonstrated that a meaningful partitioning into local models can only be accomplished in a fused space consisting of both input and output. The rst algorithm uses a batch like statistic procedure to estimate the reward ...

Analysis of Markov Renewal Reward Process on VLSI Cell Partitioning

It is well known that various characteristics in risk and queuing process can be formulated as Markov Renewal function. We study the max-position of finitely many Markov Renewal Reward process with countable state space. We define Markov Renewal equation associated with max-posed process. The solutions of the Markov Renewal Reward equation are derived and the asymptotic behaviors of the equatio...

Multi-class Classification: A Coding Based Space Partitioning

In this work we address the problem of multi-class classification in machine learning. In particular, we consider the coding approach which converts a multi-class problem to several binary classification problems by mapping the binary labeled space into several partitioned binary labeled spaces through binary channel codes. By modeling this learning problem as a communication channel, these cod...