Upgrade to Pro — share decks privately, control downloads, hide ads and more …

論文読み:Identifying Mislabeled Data using the Area Under the Margin Ranking (NeurIPS'20) /Area_Under_the_Margin_Ranking

Taro Nakasone
October 01, 2022

論文読み:Identifying Mislabeled Data using the Area Under the Margin Ranking (NeurIPS'20) /Area_Under_the_Margin_Ranking

Taro Nakasone

October 01, 2022
Tweet

More Decks by Taro Nakasone

Other Decks in Research

Transcript

  1. ઌߦݚڀ nଟஈύΠϓϥΠϯ[e.g.1,2]΍ϩόετͳଛࣦؔ਺[e.g.3,4] Λ༻͍ͯαϯϓϧΛࣝผ͢Δํ๏͕ݚڀ͞Ε͍ͯΔ [1] P. Chen, B. Liao, G. Chen,

    and S. Zhang. Understanding and utilizing deep neural networks trained with noisy labels. In ICML, 2019. [2] J. Han, P. Luo, and X. Wang. Deep self-learning from noisy labels. In CVPR, 2019. [3] Y. Xu, P. Cao, Y. Kong, and Y. Wang. LDMI: An information-theoretic noise-robust loss function. In NeurIPS, 2019. [4] Z. Zhang and M. R. Sabuncu. Generalized cross entropy loss for training deep neural networks with noisy labels. In NeurIPS, 2018
  2. ఏҊख๏ɿ nϓϩηεɿ  ᮢ஋αϯϓϧͷαϒηοτD!"# Λ࡞੒͢Δ  ᮢ஋αϯϓϧΛؚΉमਖ਼ֶशηοτD′$%&'( Λ࡞੒͢Δ 3. D′$%&'(

    ͰωοτϫʔΫΛ࠷ॳʹֶश཰͕Լ͕Δ·Ͱֶश˞ͤ͞ɼશ σʔλͷ"6.Λଌఆ͢Δɽ  ˋᮢ஋αϯϓϧ"6.ʢЋʣΛܭࢉ͢Δɽ  ЋΛᮢ஋ͱͯ͠ɺϥϕϧ෇͚͞ΕͨσʔλΛࣝผ͢Δ ※ 学習率が低下する前に学習を停⽌することで、ネットワークが収束し、その結果、誤ラベルサンプルを記憶してしまうことを防ぐ