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Foundations and Trends in Machine Learning, Volume 15

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Volume 15, Numbers 1-2, 2021

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Laurent Girin, Simon Leglaive, Xiaoyu Bie, Julien Diard, Thomas Hueber, Xavier Alameda-Pineda:
Dynamical Variational Autoencoders: A Comprehensive Review. 1-175

Volume 15, Number 3, 2022

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Thomas Nedelec, Clément Calauzènes, Noureddine El Karoui, Vianney Perchet:
Learning in Repeated Auctions. 176-334

Volume 15, Number 4, 2022

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Oliver Y. Feng, Ramji Venkataramanan, Cynthia Rush, Richard J. Samworth:
A Unifying Tutorial on Approximate Message Passing. 335-536

Volume 15, Number 5, 2022

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Prashanth L. A., Michael C. Fu:
Risk-Sensitive Reinforcement Learning via Policy Gradient Search. 537-693

Volume 15, Number 6, 2022

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Ryan J. Tibshirani:
Divided Differences, Falling Factorials, and Discrete Splines: Another Look at Trend Filtering and Related Problems. 694-846

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