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TREE: Tree Regularization for Efficient Execution

TREE: Tree Regularization for Efficient Execution

18 June 2024
Lena Schmid
Daniel Biebert
Christian Hakert
Kuan-Hsun Chen
Michel Lang
Markus Pauly
Jian-Jia Chen
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Papers citing "TREE: Tree Regularization for Efficient Execution"

5 / 5 papers shown
Title
FLInt: Exploiting Floating Point Enabled Integer Arithmetic for
  Efficient Random Forest Inference
FLInt: Exploiting Floating Point Enabled Integer Arithmetic for Efficient Random Forest Inference
Christian Hakert
Kuan-Hsun Chen
Jian-Jia Chen
14
4
0
09 Sep 2022
Hyperparameters and Tuning Strategies for Random Forest
Hyperparameters and Tuning Strategies for Random Forest
Philipp Probst
Marvin N. Wright
A. Boulesteix
109
1,375
0
10 Apr 2018
Beyond Sparsity: Tree Regularization of Deep Models for Interpretability
Beyond Sparsity: Tree Regularization of Deep Models for Interpretability
Mike Wu
M. C. Hughes
S. Parbhoo
Maurizio Zazzi
Volker Roth
Finale Doshi-Velez
AI4CE
112
281
0
16 Nov 2017
ranger: A Fast Implementation of Random Forests for High Dimensional
  Data in C++ and R
ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R
Marvin N. Wright
A. Ziegler
200
2,760
0
18 Aug 2015
Mondrian Forests: Efficient Online Random Forests
Mondrian Forests: Efficient Online Random Forests
Balaji Lakshminarayanan
Daniel M. Roy
Yee Whye Teh
46
216
0
10 Jun 2014
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