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Foundations and Trends in Machine Learning, Volume 18

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Volume 18, Number 1, 2025

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Fredrik Hellström, Giuseppe Durisi, Benjamin Guedj, Maxim Raginsky:
Generalization Bounds: Perspectives from Information Theory and PAC-Bayes. 1-223

Volume 18, Numbers 2-3, 2025

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Jacob Beck, Risto Vuorio, Evan Zheran Liu, Zheng Xiong, Luisa M. Zintgraf, Chelsea Finn, Shimon Whiteson:
A Tutorial on Meta-Reinforcement Learning. 224-384

Volume 18, Number 4, 2025

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Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Alex Strasser, Haiyang Yu, Yuqing Xie, Xiang Fu, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji:
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. 385-912

Volume 18, Number 5, 2025

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Saurabh Kumar, Henrik Marklund, Ashish Rao, Yifan Zhu, Hong Jun Jeon, Yueyang Liu, Benjamin Van Roy:
Continual Learning as Computationally Constrained Reinforcement Learning. 913-1053

Volume 18, Number 6, 2025

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Luca Franceschi, Michele Donini, Valerio Perrone, Aaron Klein, Cédric Archambeau, Matthias W. Seeger, Massimiliano Pontil, Paolo Frasconi:
Hyperparameter Optimization in Machine Learning. 1054-1201

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