Pushing the Envelope of Gradient Boosting Forests via Globally-Optimized Oblique Trees

Author:

Gabidolla Magzhan1,Carreira-Perpinan Miguel A.1

Affiliation:

1. University of California,Dept. CSE,Merced

Funder

NSF

Publisher

IEEE

Reference41 articles.

1. Improved Boosted Regression Forests Through Non-Greedy Tree Optimization

2. Smaller, more accurate regression forests using tree altern ating optimization;zharmagambetov;Proc of the 37th Int Conf Machine Learning (ICML 2020),0

3. Boosting. Foundations and Algorithms;schapire;Adaptive Computation and Machine Learning Series,2012

4. Looking for lumps: boosting and bagging for density estimation

5. Global refinement of random forest;ren;Proc of the 2015 IEEE Computer Society Conf Computer Vision and Pattern Recognition (CVPR'15),2015

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1. Shapley Deep Learning: A Consensus for General-Purpose Vision Systems;2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW);2023-10-02

2. Towards Better Decision Forests: Forest Alternating Optimization;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2023-06

3. Improved Multiclass AdaBoost Using Sparse Oblique Decision Trees;2022 International Joint Conference on Neural Networks (IJCNN);2022-07-18

4. Sparse Oblique Decision Trees: A Tool to Interpret Natural Language Processing Datasets;2022 International Joint Conference on Neural Networks (IJCNN);2022-07-18

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