Neural network pruning with combinatorial optimization

Posted by Hussein Hazimeh, Research Scientist, Athena Team, and Riade Benbaki, Graduate Student at MIT Modern neural networks have achieved impressive performance across a variety of applications, such as language, mathematical reasoning, and vision. However, these networks often use large architectures that require lots of computational resources. This can make it impractical to serve such models to users, especially in resource-constrained environments like wearables and smartphones. A widel...

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