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Online Learning under Adversarial Nonlinear Constraints
Neural Information Processing Systems
In many applications, learning systems are required to process continuous non-stationary data streams.
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Solving Inverse Problems via Diffusion Optimal Control Henry Li
Neural Information Processing Systems
We demonstrate that these limitations can be sidestepped by reframing the generative process as a discrete optimal control episode.
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On the Statistical Consistency of Risk-Sensitive Bayesian Decision-Making
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We compute the convergence rates of the RSVB approximate posterior and the corresponding optimal value.
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Module-wise Training of Neural Networks via the Minimizing Movement Scheme Anonymous Author(s) Affiliation Address email
Neural Information Processing Systems
End-to-end backpropagation is the standard training method of neural networks.
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Module-wise Training of Neural Networks via the Minimizing Movement Scheme
Neural Information Processing Systems
End-to-end backpropagation is the standard training method of neural networks.
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