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Estimation and Inference with Trees and Forests in High Dimensions
v1v2 (latest)

Estimation and Inference with Trees and Forests in High Dimensions

7 July 2020
Vasilis Syrgkanis
Manolis Zampetakis
ArXiv (abs)PDFHTML

Papers citing "Estimation and Inference with Trees and Forests in High Dimensions"

20 / 20 papers shown
Statistical Advantages of Oblique Randomized Decision Trees and Forests
Statistical Advantages of Oblique Randomized Decision Trees and Forests
Eliza O'Reilly
231
2
0
02 Jul 2024
Pure interaction effects unseen by Random Forests
Pure interaction effects unseen by Random ForestsComputational Statistics & Data Analysis (CSDA), 2024
Ricardo Blum
M. Hiabu
E. Mammen
J. T. Meyer
300
0
0
19 Jun 2024
Reproducibility and Geometric Intrinsic Dimensionality: An Investigation
  on Graph Neural Network Research
Reproducibility and Geometric Intrinsic Dimensionality: An Investigation on Graph Neural Network Research
Tobias Hille
Maximilian Stubbemann
Tom Hanika
AI4CE
327
0
0
13 Mar 2024
Applied Causal Inference Powered by ML and AI
Applied Causal Inference Powered by ML and AI
Victor Chernozhukov
Christian Hansen
Nathan Kallus
Martin Spindler
Vasilis Syrgkanis
CML
430
55
0
04 Mar 2024
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation
Jikai Jin
Vasilis Syrgkanis
CML
610
6
0
22 Feb 2024
Consistency of Random Forest Type Algorithms under a Probabilistic
  Impurity Decrease Condition
Consistency of Random Forest Type Algorithms under a Probabilistic Impurity Decrease Condition
Ricardo Blum
M. Hiabu
E. Mammen
J. T. Meyer
264
3
0
04 Sep 2023
Synthetic Combinations: A Causal Inference Framework for Combinatorial
  Interventions
Synthetic Combinations: A Causal Inference Framework for Combinatorial InterventionsNeural Information Processing Systems (NeurIPS), 2023
Abhineet Agarwal
Anish Agarwal
Suhas Vijaykumar
CML
350
11
0
24 Mar 2023
Orthogonal Series Estimation for the Ratio of Conditional Expectation
  Functions
Orthogonal Series Estimation for the Ratio of Conditional Expectation Functions
Kazuhiko Shinoda
T. Hoshino
CML
227
0
0
26 Dec 2022
Consistency of Oblique Decision Tree and its Boosting and Random Forest
Consistency of Oblique Decision Tree and its Boosting and Random Forest
Haoran Zhan
Yu Liu
Yingcun Xia
293
4
0
23 Nov 2022
Convergence Rates of Oblique Regression Trees for Flexible Function
  Libraries
Convergence Rates of Oblique Regression Trees for Flexible Function LibrariesAnnals of Statistics (Ann. Stat.), 2022
M. D. Cattaneo
Rajita Chandak
Jason M. Klusowski
291
18
0
26 Oct 2022
FACT: High-Dimensional Random Forests Inference
FACT: High-Dimensional Random Forests Inference
Chien-Ming Chi
Yingying Fan
Jinchi Lv
415
2
0
04 Jul 2022
Fast Instrument Learning with Faster Rates
Fast Instrument Learning with Faster RatesNeural Information Processing Systems (NeurIPS), 2022
Ziyu Wang
Yuhao Zhou
Chao Ding
422
5
0
22 May 2022
Label Ranking through Nonparametric Regression
Label Ranking through Nonparametric RegressionInternational Conference on Machine Learning (ICML), 2021
Eleni Psaroudaki
Alkis Kalavasis
Eleni Psaroudaki
320
4
0
04 Nov 2021
A cautionary tale on fitting decision trees to data from additive
  models: generalization lower bounds
A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds
Yan Shuo Tan
Abhineet Agarwal
Bin Yu
256
14
0
18 Oct 2021
Automatic Debiased Machine Learning via Riesz Regression
Automatic Debiased Machine Learning via Riesz Regression
Victor Chernozhukov
Whitney Newey
Victor Quintas-Martinez
Vasilis Syrgkanis
OODCML
409
26
0
30 Apr 2021
Large Scale Prediction with Decision Trees
Large Scale Prediction with Decision TreesJournal of the American Statistical Association (JASA), 2021
Jason M. Klusowski
Peter M. Tian
451
67
0
28 Apr 2021
Increasing the efficiency of randomized trial estimates via linear
  adjustment for a prognostic score
Increasing the efficiency of randomized trial estimates via linear adjustment for a prognostic scoreThe International Journal of Biostatistics (Int J Biostat), 2020
Alejandro Schuler
D. Walsh
D.F. Hall
J. Walsh
Charles K. Fisher
373
59
0
17 Dec 2020
Automatic Debiased Machine Learning of Causal and Structural Effects
Automatic Debiased Machine Learning of Causal and Structural Effects
Victor Chernozhukov
Whitney Newey
Rahul Singh
CMLAI4CE
718
145
0
14 Sep 2018
Regularized Orthogonal Machine Learning for Nonlinear Semiparametric
  Models
Regularized Orthogonal Machine Learning for Nonlinear Semiparametric Models
Denis Nekipelov
Vira Semenova
Vasilis Syrgkanis
652
22
0
13 Jun 2018
Debiased Machine Learning of Set-Identified Linear Models
Debiased Machine Learning of Set-Identified Linear ModelsJournal of Econometrics (JE), 2017
Vira Semenova
691
7
0
28 Dec 2017
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