A kernel test for causal association via noise contrastive backdoor adjustment

A kernel test for causal association via noise contrastive backdoor adjustment

Causal inference grows increasingly complex as the dimension of confounders increases. Given treatments X𝑋, outcomes Y𝑌, and measured confounders Z𝑍, we develop a non-parametric method to test the do-null hypothesis that, after an intervention on X𝑋, there is no marginal dependence of Y𝑌 on X𝑋, agai...

पूर्ण विवरण

ग्रंथसूची विवरण
मुख्य लेखकों:	Hu, R, Sejdinovic, D, Evans, RJ
स्वरूप:	Journal article
भाषा:	English
प्रकाशित:	Journal of Machine Learning Research 2024

समान संसाधन

Causal inference via Kernel deviance measures
द्वारा: Mitrovic, J, और अन्य
प्रकाशित: (2018)

Differentiable causal backdoor discovery
द्वारा: Gultchin, L, और अन्य
प्रकाशित: (2020)

Noise contrastive meta-learning for conditional density estimation using kernel mean embeddings
द्वारा: Ton, J-F, और अन्य
प्रकाशित: (2021)

An Out-of-Distribution Generalization Framework Based on Variational Backdoor Adjustment
द्वारा: Hang Su, और अन्य
प्रकाशित: (2023-12-01)

Selection, ignorability and challenges with causal fairness
द्वारा: Fawkes, J, और अन्य
प्रकाशित: (2022)

Backdoor defense method in federated learning based on contrastive training
द्वारा: Jiale ZHANG, और अन्य
प्रकाशित: (2024-03-01)

Backdoor defense method in federated learning based on contrastive training
द्वारा: Jiale ZHANG, और अन्य
प्रकाशित: (2024-03-01)

Hypothesis testing using pairwise distances and associated kernels
द्वारा: Sejdinovic, D, और अन्य
प्रकाशित: (2012)

Detecting All-to-One Backdoor Attacks in Black-Box DNNs via Differential Robustness to Noise
द्वारा: Hao Fu, और अन्य
प्रकाशित: (2025-01-01)

Text Select-Backdoor: Selective Backdoor Attack for Text Recognition Systems
द्वारा: Hyun Kwon, और अन्य
प्रकाशित: (2024-01-01)

A kernel test for three-variable interactions
द्वारा: Sejdinovic, D, और अन्य
प्रकाशित: (2013)

Bayesian kernel two-sample testing
द्वारा: Zhang, Q, और अन्य
प्रकाशित: (2022)

Large-scale kernel methods for independence testing
द्वारा: Zhang, Q, और अन्य
प्रकाशित: (2017)

Implementing a Multitarget Backdoor Attack Algorithm Based on Procedural Noise Texture Features
द्वारा: Qian Liu, और अन्य
प्रकाशित: (2024-01-01)

A differentially private kernel two-sample test
द्वारा: Raj, A, और अन्य
प्रकाशित: (2020)

Backdoor attacks in neural networks
द्वारा: Liew, Sher Yun
प्रकाशित: (2024)

Spectral Signatures in Backdoor Attacks
द्वारा: Tran, Brandon, और अन्य
प्रकाशित: (2021)

Spectral Signatures in Backdoor Attacks
द्वारा: Tran, Brandon, और अन्य
प्रकाशित: (2021)

Coronabonds : backdoor to collective debt?
द्वारा: Kliem, Frederick
प्रकाशित: (2020)

Backdoor attacks in neural networks
द्वारा: Low, Wen Wen
प्रकाशित: (2023)

CLB-Defense: based on contrastive learning defense for graph neural network against backdoor attack
द्वारा: Jinyin CHEN, और अन्य
प्रकाशित: (2023-04-01)

CLB-Defense: based on contrastive learning defense for graph neural network against backdoor attack
द्वारा: Jinyin CHEN, और अन्य
प्रकाशित: (2023-04-01)

A kernel log-rank test of independence for right-censored data
द्वारा: Fernández, T, और अन्य
प्रकाशित: (2021)

Testing and learning on distributions with symmetric noise invariance
द्वारा: Law, H, और अन्य
प्रकाशित: (2018)

Backdoors into heterogeneous classes of SAT and CSP
द्वारा: Gaspers, S, और अन्य
प्रकाशित: (2014)

Backdoors into heterogeneous classes of SAT and CSP
द्वारा: Gaspers, S, और अन्य
प्रकाशित: (2016)

Backdoors into heterogeneous classes of SAT and CSP
द्वारा: Gaspers, S, और अन्य
प्रकाशित: (2016)

Defense of hidden backdoor technology for Web
द्वारा: Liyue CHEN, और अन्य
प्रकाशित: (2020-05-01)

Defense of hidden backdoor technology for Web
द्वारा: Liyue CHEN, और अन्य
प्रकाशित: (2020-05-01)

Large scale tensor regression using kernels and variational inference
द्वारा: Hu, R, और अन्य
प्रकाशित: (2021)

A kernel- and optimal transport- based test of independence between covariates and right-censored lifetimes
द्वारा: Rindt, D, और अन्य
प्रकाशित: (2020)

Backdoor attacks against deep image compression via adaptive frequency trigger
द्वारा: Yu, Yi, और अन्य
प्रकाशित: (2023)

REGRESI NONPARAMETRIK KERNEL ADJUSTED
द्वारा: , NOVITA EKA CHANDRA, और अन्य
प्रकाशित: (2014)

Bayesian learning of kernel embeddings
द्वारा: Filippi, S, और अन्य
प्रकाशित: (2016)

Poisson intensity estimation with reproducing kernels
द्वारा: Flaxman, S, और अन्य
प्रकाशित: (2017)

Poisson intensity estimation with reproducing kernels
द्वारा: Flaxman, S, और अन्य
प्रकाशित: (2017)

Optimal kernel choice for large-scale two-sample tests
द्वारा: Gretton, A, और अन्य
प्रकाशित: (2012)

Large scale methods for kernels, causal inference and survival modelling
द्वारा: Hu, R
प्रकाशित: (2022)

Backdoor in deep learning: new threats and opportunities
द्वारा: Chen, Kangjie
प्रकाशित: (2025)

Survey on backdoor attacks targeted on neural network
द्वारा: Qingyin TAN, और अन्य
प्रकाशित: (2021-06-01)