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Inverse Factorized Soft Q-Learning for Cooperative Multi-agent Imitation Learning
Neural Information Processing Systems
In a single-agent setting, IL was shown to be done efficiently via an inverse soft-Q learning process.
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Universality of AdaGrad Stepsizes for Stochastic Optimization: Inexact Oracle, Acceleration and Variance Reduction Anton Rodomanov CISPA
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Lipschitz gradient, without needing to know neither the corresponding Lipschitz constants, nor the oracle's variance but enjoying the rates which are characteristic for algorithms which have the
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Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement Zhehao Huang, Xinwen Cheng, JingHao Zheng, Haoran Wang, Zhengbao He, Tao Li, Xiaolin Huang Shanghai Jiao Tong University
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However, computing the second-order Hessian for large-scale models is intractable.
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UltraMedical: Building Specialized Generalists in Biomedicine
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Exploring how to build open-source, GPT-4-level LLMs in the field of biomedicine is underway.
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