Reviews: Combinatorial Inference against Label Noise

The combinatorial (meta- or super-class) idea is interesting: it is reasonable and one easily expects to work well. In terms of related work, I suggest add 2 related papers. One is ECOC (Solving Multiclass Learning Problems via Error-Correcting Output Codes, JAIR 1995), which is a classic combinatorial method for classification. The other one is PENCIL (Probabilistic End-to-end Noise Correction for Learning with Noisy Labels, CVPR 2019), which is a novel noise handling method. With regard to the method, the proposed probabilistic way to decipher class from meta-class is simple.