Cover Image

META-ANOVA: Screening interactions for interpretable machine learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Choi, Yongchan, Park, Seokhun, Park, Chanmoo, Kim, Dongha, Kim, Yongdai
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Statistics Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Tensor Product Neural Networks for Functional ANOVA Model
by: Park, Seokhun, et al.
Published: (2025)

Bayesian Additive Regression Trees for functional ANOVA model
by: Park, Seokhun, et al.
Published: (2025)

Bayesian Neural Networks for Functional ANOVA model
by: Park, Seokhun, et al.
Published: (2025)

Transfer Learning for Benign Overfitting in High-Dimensional Linear Regression
by: Kim, Yeichan, et al.
Published: (2025)

A Composite Activation Function for Learning Stable Binary Representations
by: Park, Seokhun, et al.
Published: (2026)

Distributionally Robust Instrumental Variables Estimation
by: Qu, Zhaonan, et al.
Published: (2024)

A Stein Gradient Descent Approach for Doubly Intractable Distributions
by: Lee, Heesang, et al.
Published: (2024)

Computational-Statistical Trade-off in Kernel Two-Sample Testing with Random Fourier Features
by: Choi, Ikjun, et al.
Published: (2024)

Robust Estimation in metric spaces: Achieving Exponential Concentration with a Fréchet Median
by: Kim, Jakwang, et al.
Published: (2025)

A review of predictive uncertainty estimation with machine learning
by: Tyralis, Hristos, et al.
Published: (2022)

Convex Distance Operator Transport: A Convex and Geometry-Preserving Formulation
by: Chung, Junhyoung, et al.
Published: (2026)

A probabilistic view on Riemannian machine learning models for SPD matrices
by: de Surrel, Thibault, et al.
Published: (2025)

Test-time Alignment of Diffusion Models without Reward Over-optimization
by: Kim, Sunwoo, et al.
Published: (2025)

Information-Geometric Decomposition of Generalization Error in Unsupervised Learning
by: Kim, Gilhan
Published: (2026)

Nonparametric Estimation of Joint Entropy via Partitioned Sample-Spacing
by: Ho, Jungwoo, et al.
Published: (2025)

Semiparametric inference for impulse response functions using double/debiased machine learning
by: Ballinari, Daniele, et al.
Published: (2024)

Statistical Agnostic Regression: a machine learning method to validate regression models
by: Gorriz, Juan M, et al.
Published: (2024)

Adaptive debiased machine learning using data-driven model selection techniques
by: van der Laan, Lars, et al.
Published: (2023)

Decomposition of Spillover Effects Under Misspecification: Pseudo-true Estimands and a Local-Global Extension
by: Park, Yechan, et al.
Published: (2026)

Categorical and geometric methods in statistical, manifold, and machine learning
by: Lê, Hông Vân, et al.
Published: (2025)

Iteratively reweighted kernel machines efficiently learn sparse functions
by: Zhu, Libin, et al.
Published: (2025)

Learning Massive-scale Partial Correlation Networks in Clinical Multi-omics Studies with HP-ACCORD
by: Lee, Sungdong, et al.
Published: (2024)

When are dynamical systems learned from time series data statistically accurate?
by: Park, Jeongjin, et al.
Published: (2024)

A comparative study of conformal prediction methods for valid uncertainty quantification in machine learning
by: Dewolf, Nicolas
Published: (2024)

Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting
by: Hasson, Hilaf, et al.
Published: (2023)

ODIM: Outlier Detection via Likelihood of Under-Fitted Generative Models
by: Kim, Dongha, et al.
Published: (2023)

General Frameworks for Conditional Two-Sample Testing
by: Lee, Seongchan, et al.
Published: (2024)

Extended Fiducial Inference: Toward an Automated Process of Statistical Inference
by: Liang, Faming, et al.
Published: (2024)

Robust SVD Made Easy: A fast and reliable algorithm for large-scale data analysis
by: Han, Sangil, et al.
Published: (2024)

Optimal and Structure-Adaptive CATE Estimation with Kernel Ridge Regression
by: Kim, Seok-Jin
Published: (2026)

Extended Fiducial Inference for Individual Treatment Effects via Deep Neural Networks
by: Kim, Sehwan, et al.
Published: (2025)

Locally minimax optimal confidence sets for the best model
by: Kim, Ilmun, et al.
Published: (2025)

Identifiability of the minimum-trace directed acyclic graph and hill climbing algorithms without strict local optima under weakly increasing error variances
by: Chang, Hyunwoong, et al.
Published: (2025)

Dimension-agnostic inference using cross U-statistics
by: Kim, Ilmun, et al.
Published: (2020)

Sparse Max-Affine Regression
by: Kanj, Haitham, et al.
Published: (2024)

Max-Linear Regression by Convex Programming
by: Kim, Seonho, et al.
Published: (2021)

Sharp asymptotic theory for Q-learning with LDTZ learning rate and its generalization
by: Bonnerjee, Soham, et al.
Published: (2026)

Surveying the space of descriptions of a composite system with machine learning
by: Murphy, Kieran A., et al.
Published: (2024)

Physics-informed kernel learning
by: Doumèche, Nathan, et al.
Published: (2024)

Statistically guided deep learning
by: Kohler, Michael, et al.
Published: (2025)