research
∙
06/17/2023
Fair Causal Feature Selection
Causal feature selection has recently received increasing attention in m...
share
research
∙
04/24/2023
Causal Effect Estimation with Variational AutoEncoder and the Front Door Criterion
An essential problem in causal inference is estimating causal effects fr...
research
∙
11/13/2022
Towards Privacy-Aware Causal Structure Learning in Federated Setting
Causal structure learning has been extensively studied and widely used i...
research
∙
06/23/2022
Explanatory causal effects for model agnostic explanations
This paper studies the problem of estimating the contributions of featur...
research
∙
06/04/2022
Discovering Ancestral Instrumental Variables for Causal Inference from Observational Data
Instrumental variable (IV) is a powerful approach to inferring the causa...
research
∙
03/22/2022
Learning Relation-Specific Representations for Few-shot Knowledge Graph Completion
Recent years have witnessed increasing interest in few-shot knowledge gr...
research
∙
12/20/2021
Feature Selection for Efficient Local-to-Global Bayesian Network Structure Learning
Local-to-global learning approach plays an essential role in Bayesian ne...
research
∙
03/23/2021
Any Part of Bayesian Network Structure Learning
We study an interesting and challenging problem, learning any part of a ...
research
∙
03/11/2021
Causal Learner: A Toolbox for Causal Structure and Markov Blanket Learning
Causal Learner is a toolbox for learning causal structure and Markov bla...
research
∙
03/10/2021
A Local Similarity-Preserving Framework for Nonlinear Dimensionality Reduction with Neural Networks
Real-world data usually have high dimensionality and it is important to ...
research
∙
02/28/2021
Towards Efficient Local Causal Structure Learning
Local causal structure learning aims to discover and distinguish direct ...
research
∙
11/12/2020
Learning causal representations for robust domain adaptation
Domain adaptation solves the learning problem in a target domain by leve...
research
∙
03/25/2020
A general framework for causal classification
In many applications, there is a need to predict the effect of an interv...
research
∙
02/24/2020
Towards precise causal effect estimation from data with hidden variables
Causal effect estimation from observational data is a crucial but challe...
research
∙
01/28/2020
Causal query in observational data with hidden variables
This paper discusses the problem of causal query in observational data w...
research
∙
11/17/2019
Causality-based Feature Selection: Methods and Evaluations
Feature selection is a crucial preprocessing step in data analytics and ...
research
∙
02/16/2018
A Unified View of Causal and Non-causal Feature Selection
In this paper, we unify causal and non-causal feature feature selection ...
research
∙
01/25/2018
Discovering Markov Blanket from Multiple interventional Datasets
In this paper, we study the problem of discovering the Markov blanket (M...
research
∙
11/12/2016
A Review on Algorithms for Constraint-based Causal Discovery
Causal discovery studies the problem of mining causal relationships betw...
research
∙
03/02/2016