Neural Network Pruning for Compression & Understanding | Facebook AI Research | Dr. Michela Paganini

In order to contrast the explosion in size of state-of-the-art machine learning models, and due to the necessity of deploying fast, sustainable, and private on-device models on resource-constrained devices, techniques such as pruning, quantization, and distillation have emerged as strategies for model compression.

Fundamental scientific understanding of the inner workings of neural networks is necessary to build a path towards robust, efficient AI, and I will introduce research and open-source work that has facilitated the investigation of the behavior of pruned models.

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Видео Neural Network Pruning for Compression & Understanding | Facebook AI Research | Dr. Michela Paganini канала Clarifai