More from the Same Authors

• 2020 : Contributed Talk: Incentives for Federated Learning: a Hypothesis Elicitation Approach »
  Yang Liu · Jiaheng Wei
• 2021 : Linear Classifiers that Encourage Constructive Adaptation »
  Yatong Chen · Jialu Wang · Yang Liu
• 2021 : When Optimizing f-divergence is Robust with Label Noise »
  Jiaheng Wei · Yang Liu
• 2022 : Adaptive Data Debiasing Through Bounded Exploration »
  Yifan Yang · Yang Liu · Parinaz Naghizadeh
• 2023 Poster: Identifiability of Label Noise Transition Matrix »
  Yang Liu · Hao Cheng · Kun Zhang
• 2023 Poster: Model Transferability with Responsive Decision Subjects »
  Yatong Chen · Zeyu Tang · Kun Zhang · Yang Liu
• 2023 Poster: Weak Proxies are Sufficient and Preferrable for Fairness with Missing Sensitive Attributes »
  Zhaowei Zhu · Yuanshun Yao · Jiankai Sun · Hang Li · Yang Liu
• 2023 Workshop: DMLR Workshop: Data-centric Machine Learning Research »
  Ce Zhang · Praveen Paritosh · Newsha Ardalani · Nezihe Merve Gürel · William Gaviria Rojas · Yang Liu · Rotem Dror · Manil Maskey · Lilith Bat-Leah · Tzu-Sheng Kuo · Luis Oala · Max Bartolo · Ludwig Schmidt · Alicia Parrish · Daniel Kondermann · Najoung Kim
• 2022 : Model Transferability With Responsive Decision Subjects »
  Yang Liu · Yatong Chen · Zeyu Tang · Kun Zhang
• 2022 Poster: Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network »
  Shuo Yang · Erkun Yang · Bo Han · Yang Liu · Min Xu · Gang Niu · Tongliang Liu
• 2022 Poster: Detecting Corrupted Labels Without Training a Model to Predict »
  Zhaowei Zhu · Zihao Dong · Yang Liu
• 2022 Poster: Understanding Instance-Level Impact of Fairness Constraints »
  Jialu Wang · Xin Eric Wang · Yang Liu
• 2022 Spotlight: Understanding Instance-Level Impact of Fairness Constraints »
  Jialu Wang · Xin Eric Wang · Yang Liu
• 2022 Spotlight: Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network »
  Shuo Yang · Erkun Yang · Bo Han · Yang Liu · Min Xu · Gang Niu · Tongliang Liu
• 2022 Poster: Metric-Fair Classifier Derandomization »
  Jimmy Wu · Yatong Chen · Yang Liu
• 2022 Poster: Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features »
  Zhaowei Zhu · Jialu Wang · Yang Liu
• 2022 Spotlight: Detecting Corrupted Labels Without Training a Model to Predict »
  Zhaowei Zhu · Zihao Dong · Yang Liu
• 2022 Spotlight: Metric-Fair Classifier Derandomization »
  Jimmy Wu · Yatong Chen · Yang Liu
• 2022 Spotlight: Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features »
  Zhaowei Zhu · Jialu Wang · Yang Liu
• 2022 Poster: To Smooth or Not? When Label Smoothing Meets Noisy Labels »
  Jiaheng Wei · Hangyu Liu · Tongliang Liu · Gang Niu · Masashi Sugiyama · Yang Liu
• 2022 Oral: To Smooth or Not? When Label Smoothing Meets Noisy Labels »
  Jiaheng Wei · Hangyu Liu · Tongliang Liu · Gang Niu · Masashi Sugiyama · Yang Liu
• 2021 Poster: Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels »
  Zhaowei Zhu · Yiwen Song · Yang Liu
• 2021 Spotlight: Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels »
  Zhaowei Zhu · Yiwen Song · Yang Liu
• 2021 Poster: Understanding Instance-Level Label Noise: Disparate Impacts and Treatments »
  Yang Liu
• 2021 Oral: Understanding Instance-Level Label Noise: Disparate Impacts and Treatments »
  Yang Liu
• 2020 Workshop: Incentives in Machine Learning »
  Boi Faltings · Yang Liu · David Parkes · Goran Radanovic · Dawn Song
• 2020 Poster: Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates »
  Yang Liu · Hongyi Guo
• 2019 Poster: Fairness without Harm: Decoupled Classifiers with Preference Guarantees »
  Berk Ustun · Yang Liu · David Parkes
• 2019 Oral: Fairness without Harm: Decoupled Classifiers with Preference Guarantees »
  Berk Ustun · Yang Liu · David Parkes