Compact Neural Representation Using Attentive Network Pruning | AISC

Channel:
Canada LLMs Explained - Aggregate Intellect - AI.SCIENCE
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Published on ● Video Link: https://www.youtube.com/watch?v=BjyyD3IcF5Y


Duration: 1:11:37
221 views
5

Speaker(s): Mahdi Biparva



Find the recording, slides, and more info at https://ai.science/e/compact-neural-representation-using-attentive-network-pruning--MXNTz9Odz6Lqn1NGCqmC


Motivation / Abstract


Pruning becomes increasingly popular as we seek to migrate deep learning to smaller mobile platforms. The paper demonstrates a pruning technique that not only outperforms baseline models, but also proves a high compression ratio is achievable with negligible loss of accuracy. It is able to achieve such results by introducing a novel hierarchical selection mechanism as the basis of pruning.


What was discussed?
- Neural Network Compression
- Topdown selection
- Pruning mechanisms




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