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ORCIDJames Zou 0001
James Y. Zou
Person information
- affiliation: Stanford University, Department of Electrical Engineering, CA, USA
- affiliation: Harvard University, School of Engineering and Applied Sciences, Cambridge, MA, USA
Other persons with the same name
- James Zou — disambiguation page
- James Zou 0002 — Microsoft Research, One Memorial Dr, Cambridge, MA, USA
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2020 – today
- 2023
[j24]Kevin E. Wu, James Y. Zou
, Howard Chang:
Machine learning modeling of RNA structures: methods, challenges and future perspectives. Briefings Bioinform. 24(4) (2023)- [j23]Xiaowei Xu, Qianjun Jia, Haiyun Yuan, Hailong Qiu, Yuhao Dong, Wen Xie, Zeyang Yao, Jiawei Zhang, Zhiqaing Nie, Xiaomeng Li, Yiyu Shi, James Y. Zou, Meiping Huang, Jian Zhuang:
A clinically applicable AI system for diagnosis of congenital heart diseases based on computed tomography images. Medical Image Anal. 90: 102953 (2023) - [j22]Andre Esteva, Jean Feng, Douwe van der Wal, Shih-Cheng Huang, Jeffry P. Simko, Sandy Devries, Emmalyn Chen, Edward M. Schaeffer, Todd M. Morgan, Yilun Sun, Amirata Ghorbani, Nikhil Naik, Dhruv Nathawani, Richard Socher, Jeff M. Michalski, Mack Roach, Thomas M. Pisansky, Jedidiah M. Monson, Farah Naz, James Wallace, Michelle J. Ferguson, Jean-Paul Bahary, James Zou, Matthew P. Lungren, Serena Yeung, Ashley E. Ross, Michael J. Kucharczyk, Luis Souhami, Leslie Ballas, Christopher A. Peters, Sandy Liu, Alexander G. Balogh, Pamela D. Randolph-Jackson, David L. Schwartz, Michael R. Girvigian, Naoyuki G. Saito, Adam Raben, Rachel A. Rabinovitch, Khalil Katato, Howard M. Sandler, Phuoc T. Tran, Daniel E. Spratt, Stephanie Pugh, Felix Y. Feng, Osama Mohamad:
Author Correction: Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials. npj Digit. Medicine 6 (2023) - [j21]Weixin Liang, Mert Yüksekgönül, Yining Mao, Eric Wu, James Zou:
GPT detectors are biased against non-native English writers. Patterns 4(7): 100779 (2023) - [c94]Lingjiao Chen, Zhihua Jin, Sabri Eyuboglu, Huamin Qu, Christopher Ré, Matei Zaharia, James Zou:
HAPI Explorer: Comprehension, Discovery, and Explanation on History of ML APIs. AAAI 2023: 16416-16418 - [c93]Yuhui Zhang, Michihiro Yasunaga, Zhengping Zhou, Jeff Z. HaoChen, James Zou, Percy Liang, Serena Yeung:
Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models. ACL (Findings) 2023: 7479-7498 - [c92]Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng, Wenlong Ji, James Zou, Linjun Zhang:
Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data. AISTATS 2023: 4348-4380 - [c91]Haotian Ye, James Zou, Linjun Zhang:
Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise. AISTATS 2023: 8968-8990 - [c90]Kevin Wu, Dominik Dahlem, Christopher Hane, Eran Halperin, James Zou:
Collecting data when missingness is unknown: a method for improving model performance given under-reporting in patient populations. CHIL 2023: 229-242 - [c89]Federico Bianchi, Pratyusha Kalluri, Esin Durmus, Faisal Ladhak, Myra Cheng, Debora Nozza, Tatsunori Hashimoto, Dan Jurafsky, James Zou, Aylin Caliskan:
Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale. FAccT 2023: 1493-1504 - [c88]Zhun Deng, Jiayao Zhang, Linjun Zhang, Ting Ye, Yates Coley, Weijie J. Su, James Zou:
FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data. ICLR 2023 - [c87]Puheng Li, James Zou, Linjun Zhang:
FaiREE: fair classification with finite-sample and distribution-free guarantee. ICLR 2023 - [c86]Mert Yüksekgönül, Federico Bianchi, Pratyusha Kalluri, Dan Jurafsky, James Zou:
When and Why Vision-Language Models Behave like Bags-Of-Words, and What to Do About It? ICLR 2023 - [c85]Mert Yüksekgönül, Maggie Wang, James Zou:
Post-hoc Concept Bottleneck Models. ICLR 2023 - [c84]Yuhui Zhang, Jeff Z. HaoChen, Shih-Cheng Huang, Kuan-Chieh Wang, James Zou, Serena Yeung:
Diagnosing and Rectifying Vision Models using Language. ICLR 2023 - [c83]Zachary Izzo, Ruishan Liu, James Zou:
Data-Driven Subgroup Identification for Linear Regression. ICML 2023: 14531-14552 - [c82]Yongchan Kwon, James Zou:
Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value. ICML 2023: 18135-18152 - [c81]Weixin Liang, Yining Mao, Yongchan Kwon, Xinyu Yang, James Zou:
Accuracy on the Curve: On the Nonlinear Correlation of ML Performance Between Data Subpopulations. ICML 2023: 20706-20724 - [c80]Shirley Wu, Mert Yüksekgönül, Linjun Zhang, James Zou:
Discover and Cure: Concept-aware Mitigation of Spurious Correlation. ICML 2023: 37765-37786 - [i121]Roxana Daneshjou, Mert Yüksekgönül, Zhuo Ran Cai, Roberto A. Novoa, James Zou:
SkinCon: A skin disease dataset densely annotated by domain experts for fine-grained model debugging and analysis. CoRR abs/2302.00785 (2023) - [i120]Yuhui Zhang, Jeff Z. HaoChen, Shih-Cheng Huang, Kuan-Chieh Wang, James Zou, Serena Yeung:
Diagnosing and Rectifying Vision Models using Language. CoRR abs/2302.04269 (2023) - [i119]Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng, Wenlong Ji, James Zou, Linjun Zhang:
Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data. CoRR abs/2302.06232 (2023) - [i118]Weixin Liang, Mert Yüksekgönül, Yining Mao, Eric Wu, James Zou:
GPT detectors are biased against non-native English writers. CoRR abs/2304.02819 (2023) - [i117]Yuzhen Mao, Zhun Deng, Huaxiu Yao, Ting Ye, Kenji Kawaguchi, James Zou:
Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks. CoRR abs/2304.03935 (2023) - [i116]Yongchan Kwon, James Zou:
Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value. CoRR abs/2304.07718 (2023) - [i115]Zachary Izzo, Ruishan Liu, James Zou:
Data-Driven Subgroup Identification for Linear Regression. CoRR abs/2305.00195 (2023) - [i114]Shirley Wu, Mert Yüksekgönül, Linjun Zhang, James Zou:
Discover and Cure: Concept-aware Mitigation of Spurious Correlation. CoRR abs/2305.00650 (2023) - [i113]Weixin Liang, Yining Mao, Yongchan Kwon, Xinyu Yang, James Zou:
Accuracy on the Curve: On the Nonlinear Correlation of ML Performance Between Data Subpopulations. CoRR abs/2305.02995 (2023) - [i112]Lingjiao Chen, Matei Zaharia, James Zou:
FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance. CoRR abs/2305.05176 (2023) - [i111]Yuhui Zhang, Michihiro Yasunaga, Zhengping Zhou, Jeff Z. HaoChen, James Zou, Percy Liang, Serena Yeung:
Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models. CoRR abs/2305.17311 (2023) - [i110]Mert Yüksekgönül, Linjun Zhang, James Zou, Carlos Guestrin:
Beyond Confidence: Reliable Models Should Also Consider Atypicality. CoRR abs/2305.18262 (2023) - [i109]Kailas Vodrahalli, James Zou:
ArtWhisperer: A Dataset for Characterizing Human-AI Interactions in Artistic Creations. CoRR abs/2306.08141 (2023) - [i108]Kevin Fu Jiang, Weixin Liang, James Zou, Yongchan Kwon:
OpenDataVal: a Unified Benchmark for Data Valuation. CoRR abs/2306.10577 (2023) - [i107]Xinming Tu, James Zou, Weijie J. Su, Linjun Zhang:
What Should Data Science Education Do with Large Language Models? CoRR abs/2307.02792 (2023) - [i106]Lingjiao Chen, Matei Zaharia, James Zou:
How is ChatGPT's behavior changing over time? CoRR abs/2307.09009 (2023) - [i105]Jesutofunmi A. Omiye, Haiwen Gui, Shawheen J. Rezaei, James Zou, Roxana Daneshjou:
Large language models in medicine: the potentials and pitfalls. CoRR abs/2309.00087 (2023) - [i104]Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, Paul Röttger, Dan Jurafsky, Tatsunori Hashimoto, James Zou:
Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions. CoRR abs/2309.07875 (2023) - [i103]Yongchan Kwon, Eric Wu, Kevin Wu, James Zou:
DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models. CoRR abs/2310.00902 (2023) - [i102]Weixin Liang, Yuhui Zhang, Hancheng Cao, Binglu Wang, Daisy Ding, Xinyu Yang, Kailas Vodrahalli, Siyu He, Daniel Smith, Yian Yin, Daniel A. McFarland, James Zou:
Can large language models provide useful feedback on research papers? A large-scale empirical analysis. CoRR abs/2310.01783 (2023) - [i101]Chenhang Cui, Yiyang Zhou, Xinyu Yang, Shirley Wu, Linjun Zhang, James Zou, Huaxiu Yao:
Holistic Analysis of Hallucination in GPT-4V(ision): Bias and Interference Challenges. CoRR abs/2311.03287 (2023) - [i100]Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G. Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlas, Ahmed Alaa, Adji Bousso Dieng, Natasha F. Noy, Vijay Janapa Reddi, James Zou, Praveen K. Paritosh, Mihaela van der Schaar, Kurt D. Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson:
DMLR: Data-centric Machine Learning Research - Past, Present and Future. CoRR abs/2311.13028 (2023) - [i99]Lingjiao Chen, Bilge Acun, Newsha Ardalani, Yifan Sun, Feiyang Kang, Hanrui Lyu, Yongchan Kwon, Ruoxi Jia, Carole-Jean Wu, Matei Zaharia, James Zou:
Data Acquisition: A New Frontier in Data-centric AI. CoRR abs/2311.13712 (2023) - [i98]Angela Zhang, Mert Yüksekgönül, Joshua Guild, James Zou, Joseph C. Wu:
ChatGPT Exhibits Gender and Racial Biases in Acute Coronary Syndrome Management. CoRR abs/2311.14703 (2023) - 2022
- [j20]Amirata Ghorbani, Dina Berenbaum, Maor Ivgi, Yuval Dafna, James Y. Zou:
Beyond Importance Scores: Interpreting Tabular ML by Visualizing Feature Semantics. Inf. 13(1): 15 (2022) - [j19]Cameron Buckner, Risto Miikkulainen, Stephanie Forrest, Silvia Milano, James Zou, Carina Prunk, Christopher Irrgang, I. Glenn Cohen, Hao Su, Robin R. Murphy, Russell H. Taylor, Axel Krieger, Mirko Kovac, Jathan Sadowski, Vidushi Marda:
AI reflections in 2021. Nat. Mach. Intell. 4(1): 5-10 (2022) - [j18]Weixin Liang, Girmaw Abebe Tadesse, Daniel E. Ho, Li Fei-Fei, Matei Zaharia, Ce Zhang, James Zou:
Advances, challenges and opportunities in creating data for trustworthy AI. Nat. Mach. Intell. 4(8): 669-677 (2022) - [j17]Weixin Liang, Girmaw Abebe Tadesse, Daniel E. Ho, Li Fei-Fei, Matei Zaharia, Ce Zhang, James Zou:
Author Correction: Advances, challenges and opportunities in creating data for trustworthy AI. Nat. Mac. Intell. 4(10): 904 (2022) - [j16]Andre Esteva, Jean Feng, Douwe van der Wal, Shih-Cheng Huang, Jeffry P. Simko, Sandy Devries, Emmalyn Chen, Edward M. Schaeffer, Todd M. Morgan, Yilun Sun, Amirata Ghorbani, Nikhil Naik, Dhruv Nathawani, Richard Socher, Jeff M. Michalski, Mack Roach, Thomas M. Pisansky, Jedidiah M. Monson, Farah Naz, James Wallace, Michelle J. Ferguson, Jean-Paul Bahary, James Zou, Matthew P. Lungren, Serena Yeung, Ashley E. Ross, Michael J. Kucharczyk, Luis Souhami, Leslie Ballas, Christopher A. Peters, Sandy Liu, Alexander G. Balogh, Pamela D. Randolph-Jackson, David L. Schwartz, Michael R. Girvigian, Naoyuki G. Saito, Adam Raben, Rachel A. Rabinovitch, Khalil Katato, Howard M. Sandler, Phuoc T. Tran, Daniel E. Spratt, Stephanie Pugh, Felix Y. Feng, Osama Mohamad:
Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials. npj Digit. Medicine 5 (2022) - [j15]Weixin Liang, Scott Elrod, Daniel A. McFarland, James Zou:
Systematic analysis of 50 years of Stanford University technology transfer and commercialization. Patterns 3(9): 100584 (2022) - [j14]Yongchan Kwon, Tony Ginart, James Zou:
Competition over data: how does data purchase affect users? Trans. Mach. Learn. Res. 2022 (2022) - [c79]Ruishan Liu, James Zou:
Data Sculpting: Interpretable Algorithm for End-to-End Cohort Selection. IEEECONF 2022: 263-270 - [c78]Amirata Ghorbani, Andre Esteva, James Zou:
Grading of Prostate Whole-slide Images Using Weak Self-supervised Learning. IEEECONF 2022: 1439-1443 - [c77]Amirata Ghorbani, James Zou, Andre Esteva:
Data Shapley Valuation for Efficient Batch Active Learning. IEEECONF 2022: 1456-1462 - [c76]Kailas Vodrahalli, Roxana Daneshjou, Tobias Gerstenberg, James Zou:
Do Humans Trust Advice More if it Comes from AI?: An Analysis of Human-AI Interactions. AIES 2022: 763-777 - [c75]Tony Ginart, Martin Jinye Zhang, James Zou:
MLDemon: Deployment Monitoring for Machine Learning Systems. AISTATS 2022: 3962-3997 - [c74]Zachary Izzo, James Zou, Lexing Ying:
How to Learn when Data Gradually Reacts to Your Model. AISTATS 2022: 3998-4035 - [c73]Yongchan Kwon, James Zou:
Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning. AISTATS 2022: 8780-8802 - [c72]Tarek Naous, Srinjay Sarkar, Abubakar Abid, James Zou:
Clustering Plotted Data by Image Segmentation. CVPR 2022: 21467-21472 - [c71]Sabri Eyuboglu, Bojan Karlas, Christopher Ré, Ce Zhang, James Zou:
dcbench: a benchmark for data-centric AI systems. DEEM@SIGMOD 2022: 9:1-9:4 - [c70]Nazneen Rajani, Weixin Liang, Lingjiao Chen, Margaret Mitchell, James Zou:
SEAL: Interactive Tool for Systematic Error Analysis and Labeling. EMNLP (Demos) 2022: 359-370 - [c69]Lingjiao Chen, Matei Zaharia, James Zou:
How Did the Model Change? Efficiently Assessing Machine Learning API Shifts. ICLR 2022 - [c68]Sabri Eyuboglu, Maya Varma, Khaled Kamal Saab, Jean-Benoit Delbrouck, Christopher Lee-Messer, Jared Dunnmon, James Zou, Christopher Ré:
Domino: Discovering Systematic Errors with Cross-Modal Embeddings. ICLR 2022 - [c67]Weixin Liang, James Zou:
MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts. ICLR 2022 - [c66]Abubakar Abid, Mert Yüksekgönül, James Zou:
Meaningfully debugging model mistakes using conceptual counterfactual explanations. ICML 2022: 66-88 - [c65]Lingjiao Chen, Matei Zaharia, James Zou:
Efficient Online ML API Selection for Multi-Label Classification Tasks. ICML 2022: 3716-3746 - [c64]Huaxiu Yao, Yu Wang, Sai Li, Linjun Zhang, Weixin Liang, James Zou, Chelsea Finn:
Improving Out-of-Distribution Robustness via Selective Augmentation. ICML 2022: 25407-25437 - [c63]Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou:
When and How Mixup Improves Calibration. ICML 2022: 26135-26160 - [c62]Kyle Swanson, Howard Chang, James Zou:
Predicting Immune Escape with Pretrained Protein Language Model Embeddings. MLCB 2022: 110-130 - [c61]Lingjiao Chen, Zhihua Jin, Sabri Eyuboglu, Christopher Ré, Matei Zaharia, James Y. Zou:
HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions. NeurIPS 2022 - [c60]Lingjiao Chen, Matei Zaharia, James Y. Zou:
Estimating and Explaining Model Performance When Both Covariates and Labels Shift. NeurIPS 2022 - [c59]Roxana Daneshjou, Mert Yüksekgönül, Zhuo Ran Cai, Roberto A. Novoa, James Y. Zou:
SkinCon: A skin disease dataset densely annotated by domain experts for fine-grained debugging and analysis. NeurIPS 2022 - [c58]Yongchan Kwon, James Y. Zou:
WeightedSHAP: analyzing and improving Shapley based feature attributions. NeurIPS 2022 - [c57]Weixin Liang, Yuhui Zhang, Yongchan Kwon, Serena Yeung, James Y. Zou:
Mind the Gap: Understanding the Modality Gap in Multi-modal Contrastive Representation Learning. NeurIPS 2022 - [c56]Kailas Vodrahalli, Tobias Gerstenberg, James Y. Zou:
Uncalibrated Models Can Improve Human-AI Collaboration. NeurIPS 2022 - [c55]Huaxiu Yao, Yiping Wang, Linjun Zhang, James Y. Zou, Chelsea Finn:
C-Mixup: Improving Generalization in Regression. NeurIPS 2022 - [i97]Huaxiu Yao, Yu Wang, Sai Li, Linjun Zhang, Weixin Liang, James Zou, Chelsea Finn:
Improving Out-of-Distribution Robustness via Selective Augmentation. CoRR abs/2201.00299 (2022) - [i96]Antonio Ginart, Laurens van der Maaten, James Zou, Chuan Guo:
Submix: Practical Private Prediction for Large-Scale Language Models. CoRR abs/2201.00971 (2022) - [i95]Yongchan Kwon, Antonio Ginart, James Zou:
Competition over data: how does data purchase affect users? CoRR abs/2201.10774 (2022) - [i94]Kailas Vodrahalli, Tobias Gerstenberg, James Zou:
Uncalibrated Models Can Improve Human-AI Collaboration. CoRR abs/2202.05983 (2022) - [i93]Weixin Liang, James Zou:
MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts. CoRR abs/2202.06523 (2022) - [i92]Weixin Liang, Yuhui Zhang, Yongchan Kwon, Serena Yeung, James Zou:
Mind the Gap: Understanding the Modality Gap in Multi-modal Contrastive Representation Learning. CoRR abs/2203.02053 (2022) - [i91]Roxana Daneshjou, Kailas Vodrahalli, Roberto A. Novoa, Melissa Jenkins, Weixin Liang, Veronica Rotemberg, Justin Ko, Susan M. Swetter, Elizabeth E. Bailey, Olivier Gevaert, Pritam Mukherjee, Michelle Phung, Kiana Yekrang, Bradley Fong, Rachna Sahasrabudhe, Johan A. C. Allerup, Utako Okata-Karigane, James Zou, Albert Chiou:
Disparities in Dermatology AI Performance on a Diverse, Curated Clinical Image Set. CoRR abs/2203.08807 (2022) - [i90]Sabri Eyuboglu, Maya Varma, Khaled Saab, Jean-Benoit Delbrouck, Christopher Lee-Messer, Jared Dunnmon, James Zou, Christopher Ré:
Domino: Discovering Systematic Errors with Cross-Modal Embeddings. CoRR abs/2203.14960 (2022) - [i89]David Ouyang, John Theurer, Nathan R. Stein, J. Weston Hughes, Pierre Elias, Bryan He, Neal Yuan, Grant Duffy, Roopinder K. Sandhu, Joseph Ebinger, Patrick Botting, Melvin Jujjavarapu, Brian Claggett, James E. Tooley, Tim Poterucha, Jonathan H. Chen, Michael Nurok, Marco Perez, Adler J. Perotte, James Y. Zou, Nancy R. Cook, Sumeet S. Chugh, Susan Cheng, Christine M. Albert:
Electrocardiographic Deep Learning for Predicting Post-Procedural Mortality. CoRR abs/2205.03242 (2022) - [i88]Jaime Roquero Gimenez, James Y. Zou:
A Unified f-divergence Framework Generalizing VAE and GAN. CoRR abs/2205.05214 (2022) - [i87]Mert Yüksekgönül, Maggie Wang, James Zou:
Post-hoc Concept Bottleneck Models. CoRR abs/2205.15480 (2022) - [i86]Zhun Deng, Jiayao Zhang, Linjun Zhang, Ting Ye, Yates Coley, Weijie J. Su, James Zou:
FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data. CoRR abs/2206.02792 (2022) - [i85]Zhiying Zhu, Weixin Liang, James Zou:
GSCLIP : A Framework for Explaining Distribution Shifts in Natural Language. CoRR abs/2206.15007 (2022) - [i84]Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Juan Ciro, Lora Aroyo, Bilge Acun, Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Tariq Kane, Christine R. Kirkpatrick, Tzu-Sheng Kuo, Jonas Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi:
DataPerf: Benchmarks for Data-Centric AI Development. CoRR abs/2207.10062 (2022) - [i83]Lingjiao Chen, Matei Zaharia, James Zou:
Estimating and Explaining Model Performance When Both Covariates and Labels Shift. CoRR abs/2209.08436 (2022) - [i82]Lingjiao Chen, Zhihua Jin, Sabri Eyuboglu, Christopher Ré, Matei Zaharia, James Zou:
HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions. CoRR abs/2209.08443 (2022) - [i81]Kailas Vodrahalli, Justin Ko, Albert S. Chiou, Roberto A. Novoa, Abubakar Abid, Michelle Phung, Kiana Yekrang, Paige Petrone, James Zou, Roxana Daneshjou:
Development and Clinical Evaluation of an AI Support Tool for Improving Telemedicine Photo Quality. CoRR abs/2209.09105 (2022) - [i80]Yongchan Kwon, James Zou:
WeightedSHAP: analyzing and improving Shapley based feature attributions. CoRR abs/2209.13429 (2022) - [i79]Kevin E. Wu, Kevin K. Yang, Rianne van den Berg, James Y. Zou, Alex X. Lu, Ava P. Amini:
Protein structure generation via folding diffusion. CoRR abs/2209.15611 (2022) - [i78]Xinyi Zhao, Weixin Liang, James Zou:
Data Budgeting for Machine Learning. CoRR abs/2210.00987 (2022) - [i77]Mert Yüksekgönül, Federico Bianchi, Pratyusha Kalluri, Dan Jurafsky, James Zou:
When and why vision-language models behave like bags-of-words, and what to do about it? CoRR abs/2210.01936 (2022) - [i76]Zhenbang Wu, Huaxiu Yao, Zhe Su, David M. Liebovitz, Lucas M. Glass, James Zou, Chelsea Finn, Jimeng Sun:
Knowledge-Driven New Drug Recommendation. CoRR abs/2210.05572 (2022) - [i75]Huaxiu Yao, Yiping Wang, Linjun Zhang, James Zou, Chelsea Finn:
C-Mixup: Improving Generalization in Regression. CoRR abs/2210.05775 (2022) - [i74]Nazneen Rajani, Weixin Liang, Lingjiao Chen, Meg Mitchell, James Zou:
SEAL : Interactive Tool for Systematic Error Analysis and Labeling. CoRR abs/2210.05839 (2022) - [i73]Haotian Ye, James Zou, Linjun Zhang:
Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise. CoRR abs/2210.11075 (2022) - [i72]Federico Bianchi, Pratyusha Kalluri, Esin Durmus, Faisal Ladhak, Myra Cheng, Debora Nozza, Tatsunori Hashimoto, Dan Jurafsky, James Zou, Aylin Caliskan:
Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale. CoRR abs/2211.03759 (2022) - [i71]Zachary Izzo, Jinsung Yoon, Sercan Ö. Arik, James Zou:
Provable Membership Inference Privacy. CoRR abs/2211.06582 (2022) - [i70]Puheng Li, James Zou, Linjun Zhang:
FaiREE: Fair Classification with Finite-Sample and Distribution-Free Guarantee. CoRR abs/2211.15072 (2022) - 2021
- [j13]Dylan Haynes, Anusri Pampari, Christina Topham, Kathryn Schwarzenberger, Michael Heath, James Zou, Teri M. Greiling:
Patient Experience Surveys Reveal Gender-Biased Descriptions of Their Care Providers. J. Medical Syst. 45(10): 90 (2021) - [j12]Abubakar Abid, Maheen Farooqi, James Zou:
Large language models associate Muslims with violence. Nat. Mach. Intell. 3(6): 461-463 (2021) - [c54]Abubakar Abid, Maheen Farooqi, James Zou:
Persistent Anti-Muslim Bias in Large Language Models. AIES 2021: 298-306 - [c53]Gal Yona, Amirata Ghorbani, James Zou:
Who's Responsible? Jointly Quantifying the Contribution of the Learning Algorithm and Data. AIES 2021: 1034-1041 - [c52]Yongchan Kwon, Manuel A. Rivas, James Zou:
Efficient Computation and Analysis of Distributional Shapley Values. AISTATS 2021: 793-801 - [c51]Tony Ginart, Eva Zhang, Yongchan Kwon, James Zou:
Competing AI: How does competition feedback affect machine learning? AISTATS 2021: 1693-1701 - [c50]Zachary Izzo, Mary Anne Smart, Kamalika Chaudhuri, James Zou:
Approximate Data Deletion from Machine Learning Models. AISTATS 2021: 2008-2016 - [c49]Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Zou:
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data. AISTATS 2021: 2845-2853 - [c48]Girmaw Abebe Tadesse, Celia Cintas, Roxana Daneshjou, Kush R. Varshney, Peter W. J. Staar, Skyler Speakman, Kenya Andrews, Chinyere Agunwa, Justin Jia, Elizabeth E. Bailey, Jules Lipoff, Ginikanwa Onyekaba, Veronica Rotemberg, Ademide Adelekun, James Y. Zou:
Racial Representation Analysis in Dermatology Academic Materials. AMIA 2021 - [c47]Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Zou:
How Does Mixup Help With Robustness and Generalization? ICLR 2021 - [c46]Zachary Izzo, Lexing Ying, James Zou:
How to Learn when Data Reacts to Your Model: Performative Gradient Descent. ICML 2021: 4641-4650 - [c45]