Efficient learning of nonparametric directed acyclic graph with statistical guarantee
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Publication:6671929
DOI10.5705/ss.202022.0272MaRDI QIDQ6671929
Shao-Gao Lv, Yibo Deng, Unnamed Author
Publication date: 27 January 2025
Published in: STATISTICA SINICA (Search for Journal in Brave)
Cites Work
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- Mercer's theorem on general domains: on the interaction between measures, kernels, and RKHSs
- CAM: causal additive models, high-dimensional order search and penalized regression
- The max-min hill-climbing Bayesian network structure learning algorithm
- Derivative reproducing properties for kernel methods in learning theory
- Additive regression and other nonparametric models
- Oracle inequalities for sparse additive quantile regression in reproducing kernel Hilbert space
- ANOVA kernels and RKHS of zero mean functions for model-based sensitivity analysis
- Causal inference in partially linear structural equation models
- Quadratic distances on probabilities: A unified foundation
- Learning theory estimates via integral operators and their approximations
- Nonparametric sparsity and regularization
- Support Vector Machines
- Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions
- 10.1162/153244303321897717
- Efficient kernel-based variable selection with sparsistency
- Efficient Learning of Quadratic Variance Function Directed Acyclic Graphs via Topological Layers
- Likelihood Ratio Tests for a Large Directed Acyclic Graph
- On causal discovery with an equal-variance assumption
- High-dimensional causal discovery under non-Gaussianity
- Identifiability of Gaussian structural equation models with equal error variances
- Constrained likelihood for reconstructing a directed acyclic Gaussian graph
- Unified Tests for Nonparametric Functions in RKHS With Kernel Selection and Regularization
- Nonlinear Causal Discovery with Confounders
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