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Leveraging Inter-LayerDependencyforPost-Training Quantization
Neural Information Processing Systems
This paper focuses on PTQ.
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12d286282e1be5431ea05262a21f415c-Paper-Conference.pdf
Neural Information Processing Systems
Knowledge distillation (KD) has been widely used to improve the test accuracy of a "student" network, by training it to mimic the soft probabilities of a trained
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ModelInversionNetworks forModel-BasedOptimization
Neural Information Processing Systems
MINs can scale to high-dimensional input spaces and leverage offline logged data for both contextual and non-contextual optimization problems.
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