![]() ![]() (Machine Learning Open Source Software Paper)Įstimating the Carbon Footprint of BLOOM, a 176B Parameter Language Model Alexandra Sasha Luccioni, Sylvain Viguier, Anne-Laure Ligozat, 2023.Īdaptive False Discovery Rate Control with Privacy Guarantee Xintao Xia, Zhanrui Cai, 2023.Ītlas: Few-shot Learning with Retrieval Augmented Language Models Gautier Izacard, Patrick Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane Dwivedi-Yu, Armand Joulin, Sebastian Riedel, Edouard Grave, 2023.Ĭonvex Reinforcement Learning in Finite Trials Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis, Marcello Restelli, 2023. Skrl: Modular and Flexible Library for Reinforcement Learning Antonio Serrano-Muñoz, Dimitrios Chrysostomou, Simon Bøgh, Nestor Arana-Arexolaleiba, 2023. (Machine Learning Open Source Software Paper) Torchhd: An Open Source Python Library to Support Research on Hyperdimensional Computing and Vector Symbolic Architectures Mike Heddes, Igor Nunes, Pere Vergés, Denis Kleyko, Danny Abraham, Tony Givargis, Alexandru Nicolau, Alexander Veidenbaum, 2023. Scalable Real-Time Recurrent Learning Using Columnar-Constructive Networks Khurram Javed, Haseeb Shah, Richard S. ![]() ![]() 2021.02.10: Volume 21 completed Volume 22 began.įairlearn: Assessing and Improving Fairness of AI Systems Hilde Weerts, Miroslav Dudík, Richard Edgar, Adrin Jalali, Roman Lutz, Michael Madaio, 2023.2021.12.02: Message from outgoing co-EiC Bernhard Schölkopf.2022.02.18: New blog post: Retrospectives from 20 Years of JMLR.2022.07.20: New special issue on climate change.Paper volumes (ISSN 1532-4435) are now published and sold by Until the end of 2004, paper volumes (ISSNġ532-4435) were published 8 times annually and sold to libraries and Final versionsĪre published electronically (ISSN 1533-7928) JMLR has a commitment to rigorous yet rapid reviewing. High-quality scholarly articles in all areas of machine learning.Īll published papers are freely available online. International forum for the electronic and paper publication of The Journal of Machine Learning Research (JMLR), established in 2000, provides an ![]()
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