MixCIT: A Kernel Based Local-Polynomial Debiased Test for Conditional Independence on Mixed-Type Data

arXiv:2607.12830 · math.ST, stat.ML · Submitted 2026-07-14 · Read on arXiv

Mengxiao Gao, Kyra Gan, Promit Ghosal

math.ST, stat.ML

Submitted: 2026-07-14

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

Terminology

• Conditional Independence — 41× in this paper · explained in 2 episodes
• Degeneracy — 36× in this paper · explained in 4 episodes
• Consistency — 28× in this paper · explained in 3 episodes
• Calibration — 14× in this paper · explained in 9 episodes
• Causal Discovery — 12× in this paper · explained in 3 episodes
• Gaussian Multiplier Bootstrap — 10× in this paper
• Embeddings — 8× in this paper · explained in 2 episodes
• Robustness — 8× in this paper · explained in 6 episodes
• Curse of Dimensionality — 6× in this paper · explained in 6 episodes
• Phase Transition — 6× in this paper · explained in 3 episodes
• Absorb — 5× in this paper · explained in 1 episode
• Inflation — 5× in this paper · explained in 2 episodes
• Mutual Information — 5× in this paper · explained in 2 episodes
• Causal Inference — 3× in this paper · explained in 5 episodes
• Hilbert Space — 3× in this paper · explained in 2 episodes
• Orthogonal Projection — 3× in this paper · explained in 2 episodes
• Sparsity — 3× in this paper · explained in 5 episodes
• Copula — 2× in this paper · explained in 2 episodes
• Exchangeability — 2× in this paper · explained in 2 episodes
• Hilbert-Schmidt Independence Criterion — 2× in this paper
• Kernel Conditional Independence — 2× in this paper
• Monotonicity — 2× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Clarity — 1× in this paper · explained in 3 episodes
• Computational Efficiency — 1× in this paper · explained in 2 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Dimensionality Reduction — 1× in this paper · explained in 2 episodes
• Formal Verification — 1× in this paper · explained in 2 episodes
• Graph Construction — 1× in this paper · explained in 3 episodes
• Heteroscedasticity — 1× in this paper · explained in 2 episodes
• Kernel Ridge Regression — 1× in this paper · explained in 2 episodes
• Selection Bias — 1× in this paper · explained in 5 episodes
• Structural Properties — 1× in this paper · explained in 2 episodes
• Theoretical Guarantees — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Universality — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Bias correction for Chatterjee's graph-based correlation coefficient
• Measuring Association on Topological Spaces Using Kernels and Geometric Graphs
• Limit theorems of Azadkia-Chatterjee's conditional graph correlation
• Sparse-Push: Communication- & Energy-Efficient Decentralized Distributed Learning over Directed & Time-Varying Graphs with non-IID Datasets

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