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iclr.cc | ||
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www.ntentional.com
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| | | | | Highlights from my favorite Deep Learning efficiency-related papers at ICLR 2020 | |
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polukhin.tech
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| | | | | Pruning: Before and After | |
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www.ntentional.com
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| | | | | Highlights from my favorite Deep Learning efficiency-related papers at ICLR 2020 | |
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www.paepper.com
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| | | Recent advances in training deep neural networks have led to a whole bunch of impressive machine learning models which are able to tackle a very diverse range of tasks. When you are developing such a model, one of the notable downsides is that it is considered a "black-box" approach in the sense that your model learns from data you feed it, but you don't really know what is going on inside the model. | ||
