One of my favorite papers recently questions a fundamental building block of machine learning: cross entropy loss. (Surprised it took until 2017 to discover focal loss, and 2020 to apply it to DNN.)
🔗 arxiv.org/abs/2002.09437
📝 Calibrating Deep Neural Networks using Focal Loss
🔗 arxiv.org/abs/2002.09437
📝 Calibrating Deep Neural Networks using Focal Loss
No matter how well you understand something mathematically, you still might be missing something that your current models just don't show you...
Intuitive understanding comes first, the math follows!
Intuitive understanding comes first, the math follows!
The code is #PyTorch (of course :-) and available here:
github.com/torrvision/foc…
If you drop this into your codebase and see improvements, let me know!
github.com/torrvision/foc…
If you drop this into your codebase and see improvements, let me know!
In the introduction they mention multi-class classification, so I presume the whole thing works fine with multi-class! (cc. @kcimc)
https://twitter.com/kcimc/status/1330975561603170304
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