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Articles

Computer Science > Machine Learning

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By William Lu, Anuran Makur
| arxiv.org
Recent work on first-order optimizers for empirical risk minimization (ERM) has suggested that smoothness of ERM loss functions in the training data, rather than in the optimization parameters, can be leveraged to improve the oracle complexity of gradient descent (GD) methods.
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Computer Science > Machine Learning

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By Anuran Makur, Japneet Singh
| arxiv.org
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[2602.24169] Fair Division Under Inaccurate Preferences

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By Daniel Halpern, Anuran Makur, Alexandros Psomas
| arxiv.org
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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