Sequential Kernel-based Conditional Independence Testing via Adaptive Betting

arXiv:2606.18993 · stat.ML, cs.LG, stat.ME · Submitted 2026-06-17 · Read on arXiv

Zheng He, Danica J. Sutherland

stat.ML, cs.LG, stat.ME

Submitted: 2026-06-17

Comments: Published at ICML 2026: https://openreview.net/forum?id=vUMdIyTs9c

Code: https://github.com/he-zh/SKCI

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Conditional Independence — 52× in this paper · explained in 2 episodes
• Kernel-based Conditional Independence — 27× in this paper
• Calibration — 21× in this paper · explained in 9 episodes
• Embeddings — 11× in this paper · explained in 2 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Regularization — 7× in this paper · explained in 3 episodes
• Inflation — 6× in this paper · explained in 2 episodes
• Hyperparameters — 5× in this paper · explained in 2 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Hilbert Space — 3× in this paper · explained in 2 episodes
• Weight Decay — 3× in this paper · explained in 2 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Decoder — 2× in this paper · explained in 2 episodes
• Kernel Ridge Regression — 2× in this paper · explained in 2 episodes
• Reproducing Kernel Hilbert Space — 2× in this paper
• Calibration Failure — 1× in this paper · explained in 2 episodes
• Causal Discovery — 1× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Disentanglement — 1× in this paper · explained in 2 episodes
• Domain Shift — 1× in this paper · explained in 7 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Reproducing Kernel Hilbert Space (RKHS) — 1× in this paper · explained in 7 episodes
• Sequential Kernel Conditional Independence — 1× in this paper
• Universality — 1× in this paper · explained in 2 episodes

Sources

• Topological Criteria for Hypothesis Testing with Finite-Precision Measurements
• Distribution-uniform anytime-valid sequential inference and the Robbins-Siegmund distributions

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