Cover Image

On the Statistical Optimality of Optimal Decision Trees

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xu, Zineng, Ghosh, Subhro, Tan, Yan Shuo
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Statistics Theory 62G08, 68Q32
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Statistical-Computational Trade-offs for Recursive Adaptive Partitioning Estimators
by: Tan, Yan Shuo, et al.
Published: (2024)

Conditionality principle under unconstrained randomness
by: Vovk, Vladimir
Published: (2024)

Optimal In-context Adaptivity and Distributional Robustness of Transformers
by: Ma, Tianyi, et al.
Published: (2025)

Least squares approximations in linear statistical inverse learning problems
by: Helin, Tapio
Published: (2022)

Efficient and Minimax Optimal In-context Nonparametric Regression with Transformers
by: Ching, Michelle, et al.
Published: (2026)

Realizable Bayes-Consistency for General Metric Losses
by: Cohen, Dan Tsir, et al.
Published: (2026)

CRPS-Optimal Binning for Univariate Conformal Regression
by: Toccaceli, Paolo
Published: (2026)

Batched Nonparametric Bandits via k-Nearest Neighbor UCB
by: Arya, Sakshi
Published: (2025)

Weak Signals and Heavy Tails: Learning Theory meets Extreme Value Analysis
by: Clémençon, Stephan, et al.
Published: (2025)

Models Parametric Analysis via Adaptive Kernel Learning
by: Norkin, Vladimir, et al.
Published: (2025)

Conformal e-prediction in the presence of confounding
by: Vovk, Vladimir, et al.
Published: (2026)

Universality of conformal prediction under the assumption of randomness
by: Vovk, Vladimir
Published: (2025)

Validity and efficiency of the conformal CUSUM procedure
by: Vovk, Vladimir, et al.
Published: (2024)

Randomness, exchangeability, and conformal prediction
by: Vovk, Vladimir
Published: (2025)

Optimal Rate of Kernel Regression in Large Dimensions
by: Lu, Weihao, et al.
Published: (2023)

On Regression in Extreme Regions
by: Clémençon, Stephan, et al.
Published: (2023)

Inductive Venn-Abers and related regressors
by: Petej, Ivan, et al.
Published: (2026)

Optimal Federated Learning for Functional Mean Estimation under Heterogeneous Privacy Constraints
by: Cai, Tony, et al.
Published: (2024)

Optimal Federated Learning for Nonparametric Regression with Heterogeneous Distributed Differential Privacy Constraints
by: Cai, T. Tony, et al.
Published: (2024)

Error Bounds for Learning with Vector-Valued Random Features
by: Lanthaler, Samuel, et al.
Published: (2023)

Fibonacci-Driven Recursive Ensembles: Algorithms, Convergence, and Learning Dynamics
by: Fokoué, Ernest
Published: (2026)

Finding a dense submatrix of a random matrix. Sharp bounds for online algorithms
by: Bhamidi, Shankar, et al.
Published: (2025)

Conformal e-testing
by: Vovk, Vladimir, et al.
Published: (2020)

Single-index models for extreme value index regression
by: Yoshida, Takuma
Published: (2022)

Asymptotic theory for extreme value generalized additive models
by: Yoshida, Takuma
Published: (2023)

A PAC-Bayes oracle inequality for sparse neural networks
by: Steffen, Maximilian F., et al.
Published: (2022)

Understanding the Effect of GCN Convolutions in Regression Tasks
by: Chen, Juntong, et al.
Published: (2024)

Physics-informed machine learning: A mathematical framework with applications to time series forecasting
by: Doumèche, Nathan
Published: (2025)

The Optimality of Kernel Classifiers in Sobolev Space
by: Lai, Jianfa, et al.
Published: (2024)

Exchangeability and randomness for infinite and finite sequences
by: Vovk, Vladimir
Published: (2025)

Constructive interpolation and generalization rates for neural ODEs: a control perspective
by: Álvarez-López, Antonio, et al.
Published: (2026)

On the Computational Efficiency of Bayesian Additive Regression Trees: An Asymptotic Analysis
by: Tan, Yan Shuo, et al.
Published: (2024)

Ranking Perspective for Tree-based Methods with Applications to Symbolic Feature Selection
by: Luo, Hengrui, et al.
Published: (2024)

Data-driven Error Estimation: Excess Risk Bounds without Class Complexity as Input
by: Krishnamurthy, Sanath Kumar, et al.
Published: (2024)

Generalized Factor Neural Network Model for High-dimensional Regression
by: Guo, Zichuan, et al.
Published: (2025)

Conformal e-prediction
by: Vovk, Vladimir
Published: (2020)

Domain Generalization by Functional Regression
by: Holzleitner, Markus, et al.
Published: (2023)

Optimal minimax rate of learning nonlocal interaction kernels
by: Wang, Xiong, et al.
Published: (2023)

Functional Extreme-PLS
by: Girard, Stéphane, et al.
Published: (2024)

Higher-Order Feature Attribution: Bridging Statistics, Explainable AI, and Topological Signal Processing
by: Butler, Kurt, et al.
Published: (2025)