conftrace_

two-sample test

51 papers

Explore in graph

Also known as

TST

Co-occurring keywords

kernel methods (1097) hypothesis testing (254) maximum mean discrepancy (164) reproducing kernel hilbert space (334) distribution testing (61) distribution comparison (16) statistical testing (98) two-sample testing (14) distribution shift (722) statistical test (47)

Papers

Minimax Optimal Two-Sample Testing under Local Differential Privacy JMLR 2025
Integral Probability Metrics Meet Neural Networks: The Radon-Kolmogorov-Smirnov Test JMLR 2025
H2ST: Hierarchical Two-Sample Tests for Continual Out-of-Distribution Detection CVPR 2025
Deep anytime-valid hypothesis testing AISTATS 2024
On the Exploration of Local Significant Differences For Two-Sample Test NIPS 2023
MMD Aggregated Two-Sample Test JMLR 2023
Minimax Nonparametric Two-Sample Test under Adversarial Losses AISTATS 2023
A Witness Two-Sample Test AISTATS 2022
Sequential Covariate Shift Detection Using Classifier Two-Sample Tests ICML 2022
Two-Sample Test with Kernel Projected Wasserstein Distance AISTATS 2022
Adversarial Attack and Defense for Non-Parametric Two-Sample Tests ICML 2022
A Kernel Two-Sample Test for Functional Data JMLR 2022
AutoML Two-Sample Test NIPS 2022
Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions JMLR 2022
Context-Aware Drift Detection ICML 2022
A permutation-free kernel two-sample test NIPS 2022
A label efficient two-sample test UAI 2022
Maximum Mean Discrepancy Test is Aware of Adversarial Attacks ICML 2021
Efficient Balanced Treatment Assignments for Experimentation AISTATS 2021
Neural Tangent Kernel Maximum Mean Discrepancy NIPS 2021
Detection and Defense of Topological Adversarial Attacks on Graphs AISTATS 2021
Efficient Statistical Tests: A Neural Tangent Kernel Approach ICML 2021
A kernel two-sample test with selection bias UAI 2021
Application of kernel hypothesis testing on set-valued data UAI 2021
Two-sample Testing Using Deep Learning AISTATS 2020