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Found 4 papers, 3 papers with code
Understanding the Effect of the Long Tail on Neural Network Compression
E. g., it has been shown that mismatches between the full and compressed models can be biased towards under-represented classes.
Going Beyond Classification Accuracy Metrics in Model Compression
With the rise in edge-computing devices, there has been an increasing demand to deploy energy and resource-efficient models.
A Programmable Approach to Neural Network Compression
Deep neural networks (DNNs) frequently contain far more weights, represented at a higher precision, than are required for the specific task which they are trained to perform.
Message Scheduling for Performant, Many-Core Belief Propagation
Belief Propagation (BP) is a message-passing algorithm for approximate inference over Probabilistic Graphical Models (PGMs), finding many applications such as computer vision, error-correcting codes, and protein-folding.
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