Supplementary to " Part-dependent Label Noise: Towards Instance-dependent Label Noise "
–Neural Information Processing Systems
We begin by introducing notation. In the main paper (Section 3), we show how to approximate instance-dependent transition matrix by exploiting part-dependent transition matrices. Note that it is more realistic that different instances have different flip rates. However, it is hard to identify these parameters without any assumption. In the main paper (Section 4), we present the experimental results on four synthetic noisy datasets, i.e., F-MNIST, SVHN, CIF AR-10, and NEWS .
Neural Information Processing Systems
Oct-2-2025, 23:16:13 GMT