Machine Learning for Causal Inference

Sheng Li, Zhixuan Chu (Herausgeber)

Buch | Softcover

XVI, 298 Seiten

2024
Springer International Publishing (Verlag)
978-3-031-35053-5 (ISBN)

Inhalt

Overview of the Book.- Causal Inference Preliminary.- Causal Effect Estimation: Basic Methodologies.- Causal Inference on Graphs.- Causal Effect Estimation: Recent Progress, Challenges, and Opportunities.- Fair Machine Learning Through the Lens of Causality.- Causal Explainable AI.- Causal Domain Generalization.- Causal Inference and Natural Language Processing.- Causal Inference and Recommendations.- Causality Encourage the Identifiability of Instance-Dependent Label Noise.- Causal Interventional Time Series Forecasting on Multi-horizon and Multi-series Data.- Continual Causal Effect Estimation.- Summary.

Produkt-Details

• Erscheinungsdatum: 27.11.2024
• Zusatzinfo: XVI, 298 p. 73 illus., 49 illus. in color.
• Verlagsort: Cham
• Sprache: englisch
• Maße: 155 x 235 mm
• Themenwelt: Mathematik / Informatik ► Informatik ► Datenbanken
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Themenwelt: Mathematik / Informatik ► Mathematik
• Themenwelt: Technik
• Schlagworte: Causal Discovery • Causality • Counterfactuals • Statistics • Treatment Effect Estimation
• ISBN-10: 3-031-35053-7 / 3031350537
• ISBN-13: 978-3-031-35053-5 / 9783031350535
• Zustand: Neuware