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Foundations and Trends in Machine Learning, Volume 16
Volume 16, Number 1, 2023
- Thomas M. Moerland, Joost Broekens, Aske Plaat, Catholijn M. Jonker:
Model-based Reinforcement Learning: A Survey. 1-118
Volume 16, Number 2, 2023
- Lingfei Wu, Yu Chen, Kai Shen, Xiaojie Guo, Hanning Gao, Shucheng Li, Jian Pei, Bo Long:
Graph Neural Networks for Natural Language Processing: A Survey. 119-328
Volume 16, Number 3, 2023
- Nicolas Guigui, Nina Miolane, Xavier Pennec:
Introduction to Riemannian Geometry and Geometric Statistics: From Basic Theory to Implementation with Geomstats. 329-493
Volume 16, Number 4, 2023
- Anastasios N. Angelopoulos, Stephen Bates:
Conformal Prediction: A Gentle Introduction. 494-591
Volume 16, Number 5, 2023
- Brandon Amos:
Tutorial on Amortized Optimization. 592-732
Volume 16, Number 6, 2023
- Xiuyuan Lu, Benjamin Van Roy, Vikranth Dwaracherla, Morteza Ibrahimi, Ian Osband, Zheng Wen:
Reinforcement Learning, Bit by Bit. 733-865
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