More from the Same Authors

• 2021 : Meaningfully Explaining a Model's Mistakes »
  · Abubakar Abid · James Zou
• 2021 : Meaningfully Explaining a Model's Mistakes »
  Abubakar Abid · James Zou
• 2021 : MetaDataset: A Dataset of Datasets for Evaluating Distribution Shifts and Training Conflicts »
  Weixin Liang · James Zou · Weixin Liang
• 2021 : Have the Cake and Eat It Too? Higher Accuracy and Less Expense when Using Multi-label ML APIs Online »
  Lingjiao Chen · James Zou · Matei Zaharia
• 2021 : Machine Learning API Shift Assessments: Change is Coming! »
  Lingjiao Chen · James Zou · Matei Zaharia
• 2021 : Do Humans Trust Advice More if it Comes from AI? An Analysis of Human-AI Interactions »
  Kailas Vodrahalli · James Zou
• 2022 : On the nonlinear correlation of ML performance across data subpopulations »
  Weixin Liang · Yining Mao · Yongchan Kwon · Xinyu Yang · James Zou
• 2022 : GSCLIP : A Framework for Explaining Distribution Shifts in Natural Language »
  Zhiying Zhu · Weixin Liang · James Zou
• 2022 : Data Sculpting: Interpretable Algorithm for End-to-End Cohort Selection »
  Ruishan Liu · James Zou
• 2022 : Data Budgeting for Machine Learning »
  Weixin Liang · James Zou
• 2022 Poster: When and How Mixup Improves Calibration »
  Linjun Zhang · Zhun Deng · Kenji Kawaguchi · James Zou
• 2022 Poster: Efficient Online ML API Selection for Multi-Label Classification Tasks »
  Lingjiao Chen · Matei Zaharia · James Zou
• 2022 Poster: Improving Out-of-Distribution Robustness via Selective Augmentation »
  Huaxiu Yao · Yu Wang · Sai Li · Linjun Zhang · Weixin Liang · James Zou · Chelsea Finn
• 2022 Spotlight: Efficient Online ML API Selection for Multi-Label Classification Tasks »
  Lingjiao Chen · Matei Zaharia · James Zou
• 2022 Spotlight: Improving Out-of-Distribution Robustness via Selective Augmentation »
  Huaxiu Yao · Yu Wang · Sai Li · Linjun Zhang · Weixin Liang · James Zou · Chelsea Finn
• 2022 Spotlight: When and How Mixup Improves Calibration »
  Linjun Zhang · Zhun Deng · Kenji Kawaguchi · James Zou
• 2021 Poster: Improving Generalization in Meta-learning via Task Augmentation »
  Huaxiu Yao · Long-Kai Huang · Linjun Zhang · Ying WEI · Li Tian · James Zou · Junzhou Huang · Zhenhui (Jessie) Li
• 2021 Spotlight: Improving Generalization in Meta-learning via Task Augmentation »
  Huaxiu Yao · Long-Kai Huang · Linjun Zhang · Ying WEI · Li Tian · James Zou · Junzhou Huang · Zhenhui (Jessie) Li
• 2021 Poster: How to Learn when Data Reacts to Your Model: Performative Gradient Descent »
  Zachary Izzo · Lexing Ying · James Zou
• 2021 Spotlight: How to Learn when Data Reacts to Your Model: Performative Gradient Descent »
  Zachary Izzo · Lexing Ying · James Zou
• 2020 Poster: A Distributional Framework For Data Valuation »
  Amirata Ghorbani · Michael Kim · James Zou
• 2019 Poster: Concrete Autoencoders: Differentiable Feature Selection and Reconstruction »
  Muhammed Fatih Balın · Abubakar Abid · James Zou
• 2019 Poster: Discovering Conditionally Salient Features with Statistical Guarantees »
  Jaime Roquero Gimenez · James Zou
• 2019 Oral: Discovering Conditionally Salient Features with Statistical Guarantees »
  Jaime Roquero Gimenez · James Zou
• 2019 Oral: Concrete Autoencoders: Differentiable Feature Selection and Reconstruction »
  Muhammed Fatih Balın · Abubakar Abid · James Zou
• 2019 Poster: Data Shapley: Equitable Valuation of Data for Machine Learning »
  Amirata Ghorbani · James Zou
• 2019 Oral: Data Shapley: Equitable Valuation of Data for Machine Learning »
  Amirata Ghorbani · James Zou
• 2018 Poster: CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions »
  Kevin Tian · Teng Zhang · James Zou
• 2018 Oral: CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions »
  Kevin Tian · Teng Zhang · James Zou