- Intervention Efficient Algorithms for Approximate Learning of Causal Graphs
2020/12/27 by Raghavendra Addanki, Andrew McGregor, Addanki, Raghavendra +3 · 1 citation
Computer Science · Mathematics · #Algorithm #Approximation algorithm #Artificial intelligence #Bayesian Modeling and Causal Inference #Causal structure #Computer science #Conditional independence #Data Structures and Algorithms (cs.DS) #Discrete mathematics #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Graph #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Mathematical optimization #Mathematics #Property testing #Set (abstract data type) #Theoretical computer science
- Local Exchangeability
2019/06/22 by Trevor Campbell, Saifuddin Syed, Campbell, Trevor +7 · 2 citations
Computer Science · Mathematics · #Applied mathematics #Artificial intelligence #Bayesian Methods and Mixture Models #Bayesian probability #Bounded function #Computer science #Conditional independence #Conditional probability distribution #Covariate #Data mining #Econometrics #Independence (probability theory) #Inference #Mathematics #Measure (data warehouse) #Permutation (music) #Probabilistic logic #Simple (philosophy) #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #Statistical hypothesis testing #Statistical inference #Statistical model #Statistics
- Testing Bayesian Networks
2016/12/09 by Clement L. Canonne, Clément L. Canonne, Ilias Diakonikolas +6 · 8 citations
Computer Science · Mathematics · #Algorithm #Artificial intelligence #Bayesian Modeling and Causal Inference #Bayesian network #Bayesian probability #Closeness #Computer science #Conditional independence #Directed acyclic graph #Graphical model #Machine Learning and Algorithms #Mathematics #Node (physics) #Statistical Methods and Inference #Theoretical computer science
- On the completeness of orientation rules for causal discovery in the presence of latent confounders and selection bias
2008/08/15 by Jiji Zhang · 97 citations
Computer Science · Mathematics · #AI-based Problem Solving and Planning #Artificial intelligence #Bayesian Modeling and Causal Inference #Causal model #Causal structure #Completeness (order theory) #Computer science #Conditional independence #Confounding #Data Mining Algorithms and Applications #Graph #Independence (probability theory) #Latent variable #Machine learning #Mathematics #Probabilistic logic #Selection (genetic algorithm) #Selection bias #Statistics #Theoretical computer science
- Instrumental Variable Estimation of Nonparametric Models
2003/09/01 by Whitney K. Newey, James L. Powell · 76 citations
Engineering · Mathematics · #Advanced Statistical Methods and Models #Applied mathematics #Conditional expectation #Conditional independence #Control Systems and Identification #Econometrics #Estimator #Identification (biology) #Instrumental variable #Least-squares function approximation #Mathematics #Nonparametric statistics #Statistical Methods and Inference #Statistics
- Using Bayesian Networks to Analyze Expression Data
2000/08/01 by Nir Friedman, Michal Linial, Iftach Nachman +1 · 2 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · #Artificial intelligence #Bayesian Modeling and Causal Inference #Bayesian inference #Bayesian network #Bayesian probability #Biology #Computational biology #Computer science #Conditional independence #Data mining #Dynamic Bayesian network #Gene #Gene Regulatory Network Analysis #Gene expression #Gene expression and cancer classification #Gene regulatory network #Genetics #Machine learning #Snapshot (computer storage) #Systems biology #Variable-order Bayesian network
- Bayesian Network Classifiers
1997/11/01 by Nir Friedman, Dan Geiger, Moises Goldszmidt +1 · 2 citations
Computer Science · #Artificial intelligence #Bayes classifier #Bayes error rate #Bayes factor #Bayes' theorem #Bayesian Modeling and Causal Inference #Bayesian network #Bayesian probability #Bayesian programming #Classifier (UML) #Computer science #Conditional independence #Data Mining Algorithms and Applications #Feature selection #Machine learning #Naive Bayes classifier #Probabilistic classification #Robustness (evolution) #Rough Sets and Fuzzy Logic #Support vector machine