Machine Learning for Causal Inference 9783031350511, 9783031350504

This book provides a deep understanding of the relationship between machine learning and causal inference. It covers a b

140 85 21MB

English Pages 544 Year 2023

Table of contents :
Cover
Front Matter
Part I. Introduction
1. Overview of the Book
2. Causal Inference Preliminary
Part II. Machine Learning and Causal Effect Estimation
3. Causal Effect Estimation: Basic Methodologies
4. Causal Inference on Graphs
5. Causal Effect Estimation: Recent Progress, Challenges, and Opportunities
Part III. Causal Inference and Trustworthy Machine Learning
6. Fair Machine Learning Through the Lens of Causality
7. Causal Explainable AI
8. Causal Domain Generalization
Part IV. Applications of Causal Inference and Machine Learning
9. Causal Inference and Natural Language Processing
10. Causal Inference and Recommendations
11. Causality Encourages the Identifiability of Instance-Dependent Label Noise
12. Causal Interventional Time Series Forecasting on Multi-horizon and Multi-series Data
13. Continual Causal Effect Estimation
14. Summary

Machine Learning for Causal Inference
9783031350511, 9783031350504

Author / Uploaded
Sheng Li
Zhixuan Chu

Similar Topics
Computers
Algorithms and Data Structures: Pattern Recognition

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