# Online Binary Space Partitioning Forests

@inproceedings{Fan2020OnlineBS, title={Online Binary Space Partitioning Forests}, author={Xuhui Fan and Bin Li and Scott Anthony Sisson}, booktitle={AISTATS}, year={2020} }

The Binary Space Partitioning-Tree~(BSP-Tree) process was recently proposed as an efficient strategy for space partitioning tasks. Because it uses more than one dimension to partition the space, the BSP-Tree Process is more efficient and flexible than conventional axis-aligned cutting strategies. However, due to its batch learning setting, it is not well suited to large-scale classification and regression problems. In this paper, we develop an online BSP-Forest framework to address this… Expand

#### 3 Citations

Baxter Permutation Process

- Computer Science, Mathematics
- NeurIPS
- 2020

A Bayesian nonparametric model for Baxter permutations (BPs), termed BP process (BPP), is proposed and applied to relational data analysis and has a high affinity with Bayesian inference. Expand

Recurrent Dirichlet Belief Networks for Interpretable Dynamic Relational Data Modelling

- Computer Science, Mathematics
- ArXiv
- 2020

The extensive experiment results on real-world data validate the advantages of the Recurrent-DBN over the state-of-the-art models in interpretable latent structure discovery and improved link prediction performance. Expand

Bayesian Nonparametric Space Partitions: A Survey

- Computer Science, Mathematics
- IJCAI
- 2021

This survey investigates the current progress of BNSP research through the following three perspectives: models, which review various strategies for generating the partitions in the space and discuss their theoretical foundation `self-consistency'; applications, which cover the current mainstream usages of BnSP models and their potential future practises; and challenges, which identify the current unsolved problems and valuable future research topics. Expand

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