Image de couverture de livre

Asymptotic Theory and Phase Transitions for Variable Importance in Quantile Regression Forests

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Nakamura, Tomoshige, Shiraishi, Hiroshi
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning Statistics Theory
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Minimax Linear Regression under the Quantile Risk
par: Hanchi, Ayoub El, et autres
Publié: (2024)

Online Quantile Regression for Nonparametric Additive Models
par: Zhan, Haoran
Publié: (2026)

Transfer Learning for High-dimensional Quantile Regression with Distribution Shift
par: Bai, Ruiqi, et autres
Publié: (2024)

Asymptotics of Random Feature Regression Beyond the Linear Scaling Regime
par: Hu, Hong, et autres
Publié: (2024)

Nonparametric Instrumental Variable Regression with Observed Covariates
par: Shen, Zikai, et autres
Publié: (2025)

Asymptotic Optimism for Tensor Regression Models with Applications to Neural Network Compression
par: Shi, Haoming, et autres
Publié: (2026)

High-Dimensional Importance-Weighted Information Criteria: Theory and Optimality
par: Cao, Yong-Syun, et autres
Publié: (2025)

Quantile Regression using Random Forest Proximities
par: Li, Mingshu, et autres
Publié: (2024)

Nested Nonparametric Instrumental Variable Regression
par: Meza, Isaac, et autres
Publié: (2021)

Asymptotic Theory of Geometric and Adaptive $k$-Means Clustering
par: Jaffe, Adam Quinn
Publié: (2022)

Bayesian Quantile Regression with Subset Selection: A Decision Analysis Perspective
par: Feldman, Joseph, et autres
Publié: (2023)

Inference on Variable Importance for Treatment Effect Heterogeneity: Shapley Values and Beyond
par: Morzywolek, Pawel, et autres
Publié: (2025)

Meta-Learning with Generalized Ridge Regression: High-dimensional Asymptotics, Optimality and Hyper-covariance Estimation
par: Jin, Yanhao, et autres
Publié: (2024)

Generalized Bayesian Additive Regression Trees: Theory and Software
par: Saha, Enakshi
Publié: (2023)

Kernel Quantile Embeddings and Associated Probability Metrics
par: Naslidnyk, Masha, et autres
Publié: (2025)

Optimal Unconstrained Self-Distillation in Ridge Regression: Strict Improvements, Precise Asymptotics, and One-Shot Tuning
par: Dang, Hien, et autres
Publié: (2026)

TrIM: Transformed Iterative Mondrian Forests for Gradient-based Dimension Reduction and High-Dimensional Regression
par: Baptista, Ricardo, et autres
Publié: (2024)

Phase Transitions for Feature Learning in Neural Networks
par: Montanari, Andrea, et autres
Publié: (2026)

Asymptotic Theory of Eigenvectors for Latent Embeddings with Generalized Laplacian Matrices
par: Fan, Jianqing, et autres
Publié: (2025)

Deep Distributional Learning with Non-crossing Quantile Network
par: Shen, Guohao, et autres
Publié: (2025)

A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression
par: Zhang, Yixuan, et autres
Publié: (2025)

A Random Matrix Theory Perspective on the Spectrum of Learned Features and Asymptotic Generalization Capabilities
par: Dandi, Yatin, et autres
Publié: (2024)

Direct Doubly Robust Estimation of Conditional Quantile Contrasts
par: Givens, Josh, et autres
Publié: (2026)

A Computational Transition for Detecting Multivariate Shuffled Linear Regression by Low-Degree Polynomials
par: Li, Zhangsong
Publié: (2025)

Disentangled Feature Importance
par: Du, Jin-Hong, et autres
Publié: (2025)

On the Precise Asymptotics of Universal Inference
par: Takatsu, Kenta
Publié: (2025)

Multiscale Asymptotic Normality in Quantile Regression: Hilbert Matrices and Polynomial Designs
par: Maanan, Saïd, et autres
Publié: (2025)

Sharp Concentration Inequalities: Phase Transition and Mixing of Orlicz Tails with Variance
par: Shen, Yinan, et autres
Publié: (2026)

Semi-Supervised Quantile Estimation: Robust and Efficient Inference in High Dimensional Settings
par: Chakrabortty, Abhishek, et autres
Publié: (2022)

Importance Weighting Correction of Regularized Least-Squares for Target Shift
par: Gogolashvili, Davit
Publié: (2022)

Exogenous Randomness Empowering Random Forests
par: Mei, Tianxing, et autres
Publié: (2024)

Phase Transition for Stochastic Block Model with more than $\sqrt{n}$ Communities
par: Carpentier, Alexandra, et autres
Publié: (2025)

Precise Asymptotics of Bagging Regularized M-estimators
par: Koriyama, Takuya, et autres
Publié: (2024)

Asymptotically Optimal Sequential Testing with Markovian Data
par: Sethi, Alhad, et autres
Publié: (2026)

Semi-supervised Fréchet Regression
par: Qiu, Rui, et autres
Publié: (2024)

Kernel Ridge Regression Inference
par: Singh, Rahul, et autres
Publié: (2023)

Bayesian Models for Joint Selection of Features and Auto-Regressive Lags: Theory and Applications in Environmental and Financial Forecasting
par: Manna, Alokesh, et autres
Publié: (2025)

Phase Transition for Stochastic Block Model with more than $\sqrt{n}$ Communities (II)
par: Carpentier, Alexandra, et autres
Publié: (2025)

Differentially Private Two-Stage Gradient Descent for Instrumental Variable Regression
par: Liang, Haodong, et autres
Publié: (2025)

Precise Asymptotics and Refined Regret of Variance-Aware UCB
par: Fan, Yingying, et autres
Publié: (2024)