:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Hasegawa, Hiroki, Tamura, Aoba, Okada, Yukihiko
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Methodology
Online Access:	https://arxiv.org/abs/2604.16894
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Robust and Non-Iterative Tensor Decomposition Method with Automatic Thresholding
by: Hasegawa, Hiroki, et al.
Published: (2025)

Interaction Tensor SHAP
by: Hasegawa, Hiroki, et al.
Published: (2025)

Collaborative causal inference on distributed data
by: Kawamata, Yuji, et al.
Published: (2022)

Estimation of conditional average treatment effects on distributed confidential data
by: Kawamata, Yuji, et al.
Published: (2024)

Learning Joint and Individual Structure in Network Data with Covariates
by: James, Carson, et al.
Published: (2024)

Prediction-Powered Inference with Imputed Covariates and Nonuniform Sampling
by: Kluger, Dan M., et al.
Published: (2025)

Spatial Covariance Constraints for Gaussian Mixture Models
by: Lu, Hanzhang, et al.
Published: (2026)

Graph Topic Modeling for Documents with Spatial or Covariate Dependencies
by: Jung, Yeo Jin, et al.
Published: (2024)

Estimating Covariate-balanced Survival Curve in Distributed Data Environment using Data Collaboration Quasi-Experiment
by: Toyoda, Akihiro, et al.
Published: (2025)

The Generalised Kernel Covariance Measure
by: Bergen, Luca, et al.
Published: (2026)

Decomposing Gaussians with Unknown Covariance
by: Dharamshi, Ameer, et al.
Published: (2024)

Covariate-assisted graph matching
by: Dawn, Trisha, et al.
Published: (2025)

Learning Linear Polytree Structural Equation Models
by: Lou, Xingmei, et al.
Published: (2021)

Covariate-assisted Grade of Membership Models via Shared Latent Geometry
by: Xu, Zhiyu, et al.
Published: (2026)

The Cellwise Minimum Covariance Determinant Estimator
by: Raymaekers, Jakob, et al.
Published: (2022)

Covariate-dependent Graphical Model Estimation via Neural Networks with Statistical Guarantees
by: Lin, Jiahe, et al.
Published: (2025)

Enhancing Signal Proportion Estimation Through Leveraging Arbitrary Covariance Structures
by: Bai, Jingtian, et al.
Published: (2025)

Principal Component Analysis When n < p: Challenges and Solutions
by: Weeraratne, Nuwan, et al.
Published: (2025)

Bayesian Counterfactual Prediction Models for HIV Care Retention with Incomplete Outcome and Covariate Information
by: Oganisian, Arman, et al.
Published: (2024)

Ensemble Prediction via Covariate-dependent Stacking
by: Wakayama, Tomoya, et al.
Published: (2024)

Accounting for Missing Covariates in Heterogeneous Treatment Estimation
by: Yamin, Khurram, et al.
Published: (2024)

Testing Hypotheses of Covariate Effects on Topics of Discourse
by: Phelan, Gabriel, et al.
Published: (2025)

Efficient Covariance Estimation for Sparsified Functional Data
by: Zheng, Sijie, et al.
Published: (2025)

Covariate-Adjusted Deep Causal Learning for Heterogeneous Panel Data Models
by: Zhou, Guanhao, et al.
Published: (2025)

A Set of Rules for Model Validation
by: Camacho, José
Published: (2025)

Covariance-Driven Regression Trees: Reducing Overfitting in CART
by: Zhang, Likun, et al.
Published: (2026)

DARTS: Targeting Prognostic Covariates in Budget-Constrained Sequential Experiments
by: Husar, Kateryna, et al.
Published: (2026)

Predicting Covariate-Driven Spatial Deformation for Nonstationary Gaussian Processes
by: Gu, Minghao, et al.
Published: (2026)

Representation Learning Preserving Ignorability and Covariate Matching for Treatment Effects
by: Nanavati, Praharsh, et al.
Published: (2025)

A Stable and Efficient Covariate-Balancing Estimator for Causal Survival Effects
by: Pham, Khiem, et al.
Published: (2023)

Low-Rank Covariance Completion for Graph Quilting with Applications to Functional Connectivity
by: Chang, Andersen, et al.
Published: (2022)

Improving Finite Sample Performance of Causal Discovery by Exploiting Temporal Structure
by: Bang, Christine W, et al.
Published: (2024)

Learning Large Causal Structures from Inverse Covariance Matrix via Sparse Matrix Decomposition
by: Dong, Shuyu, et al.
Published: (2022)

Covariate-Elaborated Robust Partial Information Transfer with Conditional Spike-and-Slab Prior
by: Zhang, Ruqian, et al.
Published: (2024)

SPARKLE: A Nonparametric Approach for Online Decision-Making with High-Dimensional Covariates
by: Wang, Wenjia, et al.
Published: (2025)

DFW: A Novel Weighting Scheme for Covariate Balancing and Treatment Effect Estimation
by: Khan, Ahmad Saeed, et al.
Published: (2025)

Robust Inference of Dynamic Covariance Using Wishart Processes and Sequential Monte Carlo
by: Huijsdens, Hester, et al.
Published: (2024)

Additive Covariance Matrix Models: Modelling Regional Electricity Net-Demand in Great Britain
by: Gioia, V., et al.
Published: (2022)

Empirical Bayes Covariance Decomposition, and a Solution to the Multiple Tuning Problem in Sparse PCA
by: Kang, Joonsuk, et al.
Published: (2023)

PCM Selector: Penalized Covariate-Mediator Selection Operator for Evaluating Linear Causal Effects
by: Nanmo, Hisayoshi, et al.
Published: (2024)