Cover Image

Generalized Data Thinning Using Sufficient Statistics

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Dharamshi, Ameer, Neufeld, Anna, Motwani, Keshav, Gao, Lucy L., Witten, Daniela, Bien, Jacob
Format:	Preprint
Published:	2023
Subjects:	Methodology Statistics Theory Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Thinning a Wishart Random Matrix
by: Dharamshi, Ameer, et al.
Published: (2025)

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

Discussion of "Data fission: splitting a single data point"
by: Neufeld, Anna, et al.
Published: (2024)

Hierarchical Clustering With Confidence
by: Wu, Di, et al.
Published: (2025)

Generalized Kernel Thinning
by: Dwivedi, Raaz, et al.
Published: (2021)

Maximum Mean Discrepancy with Unequal Sample Sizes via Generalized U-Statistics
by: Wei, Aaron, et al.
Published: (2025)

Kernel Thinning
by: Dwivedi, Raaz, et al.
Published: (2021)

Statistical Inference on Gradient Flows
by: Li, Tongyu, et al.
Published: (2026)

Statistical Properties of Rectified Flow
by: Mena, Gonzalo, et al.
Published: (2025)

A Selective Review on Statistical Methods for Massive Data Computation: Distributed Computing, Subsampling, and Minibatch Techniques
by: Li, Xuetong, et al.
Published: (2024)

Likelihood-Preserving Embeddings for Statistical Inference
by: Akdemir, Deniz
Published: (2025)

Extrapolation-Aware Nonparametric Statistical Inference
by: Pfister, Niklas, et al.
Published: (2024)

Statistical Inference for Gradient Boosting Regression
by: Fang, Haimo, et al.
Published: (2025)

Robust Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models
by: Tian, Ye, et al.
Published: (2022)

Statistical Hypothesis Testing for Information Value (IV)
by: Rojas, Helder, et al.
Published: (2023)

Extrapolation in Statistical Learning with Extreme Value Theory
by: Engelke, Sebastian, et al.
Published: (2026)

Algebraic and Statistical Properties of the Ordinary Least Squares Interpolator
by: Shen, Dennis, et al.
Published: (2023)

Scalable Kernel-Based Distances for Statistical Inference and Integration
by: Naslidnyk, Masha
Published: (2026)

Statistical Inference under Adaptive Sampling with LinUCB
by: Fan, Wei, et al.
Published: (2025)

Revisiting inference after prediction
by: Motwani, Keshav, et al.
Published: (2023)

Conditional Predictive Inference for General Structured Data with Group Symmetries
by: Shen, Yichen, et al.
Published: (2026)

Generalization Bounds and Stopping Rules for Learning with Self-Selected Data
by: Rodemann, Julian, et al.
Published: (2025)

Differentiable Structure Learning and Causal Discovery for General Binary Data
by: Deng, Chang, et al.
Published: (2025)

Stability Bounds for Smooth Optimal Transport Maps and their Statistical Implications
by: Balakrishnan, Sivaraman, et al.
Published: (2025)

Statistical and Computational Efficiency for Smooth Tensor Estimation with Unknown Permutations
by: Lee, Chanwoo, et al.
Published: (2021)

Generalized Grade-of-Membership Estimation for High-dimensional Locally Dependent Data
by: Chen, Ling, et al.
Published: (2024)

High-Dimensional Statistics: Reflections on Progress and Open Problems
by: Maleki, Arian, et al.
Published: (2026)

Statistical Inference for Manifold Similarity and Alignability across Noisy High-Dimensional Datasets
by: Chen, Hongrui, et al.
Published: (2025)

A Unified Framework for Semiparametrically Efficient Semi-Supervised Learning
by: Xu, Zichun, et al.
Published: (2025)

BELIEF in Dependence: Leveraging Atomic Linearity in Data Bits for Rethinking Generalized Linear Models
by: Brown, Benjamin, et al.
Published: (2022)

Low-Rank Thinning
by: Carrell, Annabelle Michael, et al.
Published: (2025)

On Statistical Inference for High-Dimensional Binary Time Series
by: Dai, Dehao, et al.
Published: (2025)

Debiased Nonparametric Regression for Statistical Inference and Distributionally Robustness
by: Kato, Masahiro
Published: (2024)

Towards a Unified Theory for Semiparametric Data Fusion with Individual-Level Data
by: Graham, Ellen, et al.
Published: (2024)

Minimax Signal Detection in Sparse Additive Models
by: Kotekal, Subhodh, et al.
Published: (2023)

A network-constrain Weibull AFT model for biomarkers discovery
by: Angelini, Claudia, et al.
Published: (2024)

Perturbation-based Effect Measures for Compositional Data
by: Lundborg, Anton Rask, et al.
Published: (2023)

Estimation of Treatment Effects in Extreme and Unobserved Data
by: Tan, Jiyuan, et al.
Published: (2025)

Multi-environment Invariance Learning with Missing Data
by: Jia, Yiran, et al.
Published: (2026)

Minimax Regret Learning for Data with Heterogeneous Subgroups
by: Mo, Weibin, et al.
Published: (2024)