Pruning

How to Reduce Training Parameters in CNNs While Keeping Accuracy Above 99%

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How to Reduce Training Parameters in CNNs While Keeping Accuracy Above 99%

Author: Sabrina Göllner Translator: Chen Zhiyan Proofreader: zrx This article is approximately 4800 words long and is recommended to be read in 10 minutes. This article presents research by institutions such as Niantic and UCL, which has achieved high-quality depth estimation and 3D reconstruction using a carefully designed and trained 2D network. Tags: CNN Training … Read more

Guide to Optimizing Transformer Memory Usage

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Guide to Optimizing Transformer Memory Usage

MLNLP community is a well-known machine learning and natural language processing community in China and abroad, covering NLP master’s and PhD students, university teachers, and corporate researchers. The vision of the community is to promote communication and progress between the academic and industrial fields of natural language processing and machine learning, especially for beginners. Reprinted … Read more