You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
The Code uses "lrt_correction"(LRT, ICLR2020) by default.
And the "prob_correction" seems not match PLC, it considers "cur_prob_distri[y_noise[i]]/top_probs[-1]", and no "f(x_i)-1/2,"t>=m","theta=1/2-T" can be found.
The text was updated successfully, but these errors were encountered:
The "lrt_function" is an implemention of PLC in multi-class scenario. "prob_correction" is another implemention, almost the same, and it use the argmax(f_x[x]) to replace label rather than "probabilistic label correction" when predicted confidence below threshold.
Notice that "Algorithm 1" in paper is a binary case of PLC, followed by an instruction "Generalizing to the multi-class scenario.".
The Code uses "lrt_correction"(LRT, ICLR2020) by default.
And the "prob_correction" seems not match PLC, it considers "cur_prob_distri[y_noise[i]]/top_probs[-1]", and no "f(x_i)-1/2,"t>=m","theta=1/2-T" can be found.
The text was updated successfully, but these errors were encountered: