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Found 2 papers, 1 papers with code
Constructing Multiclass Classifiers using Binary Classifiers Under Log-Loss
For this method we prove that the multiclass regret is exactly a weighted sum of constituent binary regrets where the weighing is determined by the tree structure.
Simple Modulo can Significantly Outperform Deep Learning-based Deepcode
This Modulo-SK scheme has been omitted from the performance comparisons made in the Deepcode paper, due to its use of common randomness (dither), and in a later version since it was incorrectly interpreted as a variable-length coding scheme.
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