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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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Journal Articles
- 2023
[j27]Kevin E. Wu, James Y. Zou
, Howard Chang:
Machine learning modeling of RNA structures: methods, challenges and future perspectives. Briefings Bioinform. 24(4) (2023)- [j26]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) - [j25]Eric D. Sun, Rong Ma, James Zou:
Dynamic visualization of high-dimensional data. Nat. Comput. Sci. 3(1): 86-100 (2023) - [j24]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) - [j23]J. Weston Hughes, James E. Tooley, Jessica Torres Soto, Anna Ostropolets, Tim Poterucha, Matthew Christensen, Neal Yuan, Ben Ehlert, Dhamanpreet Kaur, Guson Kang, Albert J. Rogers, Sanjiv M. Narayan, Pierre Elias, David Ouyang, Euan A. Ashley, James Zou, Marco V. Perez:
A deep learning-based electrocardiogram risk score for long term cardiovascular death and disease. npj Digit. Medicine 6 (2023) - [j22]Girmaw Abebe Tadesse, Celia Cintas, Kush R. Varshney, Peter W. J. Staar, Chinyere Agunwa, Skyler Speakman, Justin Jia, Elizabeth E. Bailey, Ademide Adelekun, Jules Lipoff, Ginikanwa Onyekaba, Jenna C. Lester, Veronica Rotemberg, James Zou, Roxana Daneshjou:
Skin Tone Analysis for Representation in Educational Materials (STAR-ED) using machine learning. 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) - 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) - 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) - 2020
- [j11]Zhenqin Wu, Nilah M. Ioannidis, James Zou, Russell Schwartz:
Predicting target genes of non-coding regulatory variants with IRT. Bioinform. 36(16): 4440-4448 (2020) - [j10]Abubakar Abid, Ali Abdalla, Ali Abid, Dawood Khan, Abdulrahman Alfozan, James Zou:
An online platform for interactive feedback in biomedical machine learning. Nat. Mach. Intell. 2(2): 86-88 (2020) - [j9]David Ouyang, Bryan He, Amirata Ghorbani, Neal Yuan, Joseph Ebinger, Curtis P. Langlotz, Paul A. Heidenreich, Robert A. Harrington, David H. Liang, Euan A. Ashley, James Y. Zou:
Video-based AI for beat-to-beat assessment of cardiac function. Nat. 580(7802): 252-256 (2020) - [j8]Amirata Ghorbani, David Ouyang, Abubakar Abid, Bryan He, Jonathan H. Chen, Robert A. Harrington, David H. Liang, Euan A. Ashley, James Y. Zou:
Deep learning interpretation of echocardiograms. npj Digit. Medicine 3 (2020) - [j7]Daniel Russo, James Zou:
How Much Does Your Data Exploration Overfit? Controlling Bias via Information Usage. IEEE Trans. Inf. Theory 66(1): 302-323 (2020) - 2019
- [j6]Anvita Gupta, James Zou:
Feedback GAN for DNA optimizes protein functions. Nat. Mach. Intell. 1(2): 105-111 (2019) - [j5]Cara Tannenbaum, Robert P. Ellis, Friederike Eyssel, James Zou, Londa Schiebinger:
Sex and gender analysis improves science and engineering. Nat. 575(7781): 137-146 (2019) - [j4]Yuhui Zhang, Allen Nie, Ashley Zehnder, Rodney López Page, James Zou:
VetTag: improving automated veterinary diagnosis coding via large-scale language modeling. npj Digit. Medicine 2 (2019) - 2018
- [j3]Allen Nie, Ashley Zehnder, Rodney López Page, Yuhui Zhang, Arturo López Pineda, Manuel A. Rivas, Carlos D. Bustamante, James Zou:
DeepTag: inferring diagnoses from veterinary clinical notes. npj Digit. Medicine 1 (2018) - [j2]Nikhil Garg, Londa Schiebinger, Dan Jurafsky, James Zou:
Word embeddings quantify 100 years of gender and ethnic stereotypes. Proc. Natl. Acad. Sci. USA 115(16): E3635-E3644 (2018) - 2015
- [j1]James Y. Zou, Eran Halperin, Esteban Gonzàlez Burchard, Sriram Sankararaman:
Inferring parental genomic ancestries using pooled semi-Markov processes. Bioinform. 31(12): 190-196 (2015)
Conference and Workshop Papers
- 2023
- [c99]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 - [c98]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 - [c97]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 - [c96]Haotian Ye, James Zou, Linjun Zhang:
Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise. AISTATS 2023: 8968-8990 - [c95]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 - [c94]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 - [c93]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 - [c92]Puheng Li, James Zou, Linjun Zhang:
FaiREE: fair classification with finite-sample and distribution-free guarantee. ICLR 2023 - [c91]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 - [c90]Mert Yüksekgönül, Maggie Wang, James Zou:
Post-hoc Concept Bottleneck Models. ICLR 2023 - [c89]Yuhui Zhang, Jeff Z. HaoChen, Shih-Cheng Huang, Kuan-Chieh Wang, James Zou, Serena Yeung:
Diagnosing and Rectifying Vision Models using Language. ICLR 2023 - [c88]Zachary Izzo, Ruishan Liu, James Zou:
Data-Driven Subgroup Identification for Linear Regression. ICML 2023: 14531-14552 - [c87]Yongchan Kwon, James Zou:
Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value. ICML 2023: 18135-18152 - [c86]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 - [c85]Shirley Wu, Mert Yüksekgönül, Linjun Zhang, James Zou:
Discover and Cure: Concept-aware Mitigation of Spurious Correlation. ICML 2023: 37765-37786 - [c84]Yiqun Chen, James Y. Zou:
TWIGMA: A dataset of AI-Generated Images with Metadata From Twitter. NeurIPS 2023 - [c83]Kevin Fu Jiang, Weixin Liang, James Y. Zou, Yongchan Kwon:
OpenDataVal: a Unified Benchmark for Data Valuation. NeurIPS 2023 - [c82]Paul Pu Liang, Zihao Deng, Martin Q. Ma, James Y. Zou, Louis-Philippe Morency, Ruslan Salakhutdinov:
Factorized Contrastive Learning: Going Beyond Multi-view Redundancy. NeurIPS 2023 - [c81]Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Alicia Parrish, Hannah Rose Kirk, Jessica Quaye, Charvi Rastogi, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Will Cukierski, Juan Ciro, Lora Aroyo, Bilge Acun, Lingjiao Chen, Mehul Raje, Max Bartolo, Evan Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Addison Howard, Oana Inel, Tariq Kane, Christine R. Kirkpatrick, D. Sculley, Tzu-Sheng Kuo, Jonas W. Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Y. Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi:
DataPerf: Benchmarks for Data-Centric AI Development. NeurIPS 2023 - [c80]Mert Yüksekgönül, Linjun Zhang, James Y. Zou, Carlos Guestrin:
Beyond Confidence: Reliable Models Should Also Consider Atypicality. NeurIPS 2023 - 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 - 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]Huaxiu Yao, Long-Kai Huang, Linjun Zhang, Ying Wei, Li Tian, James Zou, Junzhou Huang, Zhenhui Li:
Improving Generalization in Meta-learning via Task Augmentation. ICML 2021: 11887-11897 - [c44]Weixin Liang, James Zou:
Neural Group Testing to Accelerate Deep Learning. ISIT 2021: 958-963 - [c43]Antonio A. Ginart, Maxim Naumov, Dheevatsa Mudigere, Jiyan Yang, James Zou:
Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems. ISIT 2021: 2786-2791 - [c42]Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Y. Zou:
Adversarial Training Helps Transfer Learning via Better Representations. NeurIPS 2021: 25179-25191 - [c41]Kailas Vodrahalli, Roxana Daneshjou, Roberto A. Novoa, Albert Chiou, Justin M. Ko, James Zou:
TrueImage: A Machine Learning Algorithm to Improve the Quality of Telehealth Photos. PSB 2021 - 2020
- [c40]Weixin Liang, James Zou, Zhou Yu:
Beyond User Self-Reported Likert Scale Ratings: A Comparison Model for Automatic Dialog Evaluation. ACL 2020: 1363-1374 - [c39]Weixin Liang, James Zou, Zhou Yu:
ALICE: Active Learning with Contrastive Natural Language Explanations. EMNLP (1) 2020: 4380-4391 - [c38]Ruishan Liu, Akshay Balsubramani, James Zou:
Learning transport cost from subset correspondence. ICLR 2020 - [c37]Amirata Ghorbani, Michael P. Kim, James Zou:
A Distributional Framework For Data Valuation. ICML 2020: 3535-3544 - [c36]Lingjiao Chen, Matei Zaharia, James Y. Zou:
FrugalML: How to use ML Prediction APIs more accurately and cheaply. NeurIPS 2020 - [c35]Amirata Ghorbani, James Y. Zou:
Neuron Shapley: Discovering the Responsible Neurons. NeurIPS 2020 - [c34]Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Y. Zou, Sergey Levine, Chelsea Finn, Tengyu Ma:
MOPO: Model-based Offline Policy Optimization. NeurIPS 2020 - [c33]Allen Nie, Arturo L. Pineda, Matt W. Wright, Hannah Wand, Bryan Wulf, Helio A. Costa, Ronak Y. Patel, Carlos D. Bustamante, James Zou:
LitGen: Genetic Literature Recommendation Guided by Human Explanations. PSB 2020: 67-78 - 2019
- [c32]Amirata Ghorbani, Abubakar Abid, James Y. Zou:
Interpretation of Neural Networks Is Fragile. AAAI 2019: 3681-3688 - [c31]Michael P. Kim, Amirata Ghorbani, James Y. Zou:
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification. AIES 2019: 247-254 - [c30]Jaime Roquero Gimenez, Amirata Ghorbani, James Y. Zou:
Knockoffs for the Mass: New Feature Importance Statistics with False Discovery Guarantees. AISTATS 2019: 2125-2133 - [c29]Jaime Roquero Gimenez, James Y. Zou:
Improving the Stability of the Knockoff Procedure: Multiple Simultaneous Knockoffs and Entropy Maximization. AISTATS 2019: 2184-2192 - [c28]Abdi-Hakin Dirie, Abubakar Abid, James Y. Zou:
Contrastive Multivariate Singular Spectrum Analysis. Allerton 2019: 1122-1127 - [c27]Hongyao Ma, Reshef Meir, David C. Parkes, James Y. Zou:
Contingent Payment Mechanisms for Resource Utilization. AAMAS 2019: 422-430 - [c26]Muhammed Fatih Balin, Abubakar Abid, James Y. Zou:
Concrete Autoencoders: Differentiable Feature Selection and Reconstruction. ICML 2019: 444-453 - [c25]Amirata Ghorbani, James Y. Zou:
Data Shapley: Equitable Valuation of Data for Machine Learning. ICML 2019: 2242-2251 - [c24]Jaime Roquero Gimenez, James Y. Zou:
Discovering Conditionally Salient Features with Statistical Guarantees. ICML 2019: 2290-2298 - [c23]Martin J. Zhang, James Zou, David Tse:
Adaptive Monte Carlo Multiple Testing via Multi-Armed Bandits. ICML 2019: 7512-7522 - [c22]Dorottya Demszky, Nikhil Garg, Rob Voigt, James Zou, Jesse Shapiro, Matthew Gentzkow, Dan Jurafsky:
Analyzing Polarization in Social Media: Method and Application to Tweets on 21 Mass Shootings. NAACL-HLT (1) 2019: 2970-3005 - [c21]Antonio Ginart, Melody Y. Guan, Gregory Valiant, James Zou:
Making AI Forget You: Data Deletion in Machine Learning. NeurIPS 2019: 3513-3526 - [c20]Amirata Ghorbani, James Wexler, James Y. Zou, Been Kim:
Towards Automatic Concept-based Explanations. NeurIPS 2019: 9273-9282 - [c19]Martin J. Zhang, Fei Xia, James Zou:
AdaFDR: A Fast, Powerful and Covariate-Adaptive Approach to Multiple Hypothesis Testing. RECOMB 2019: 330-333 - 2018
- [c18]Xinkun Nie, Xiaoying Tian, Jonathan Taylor, James Zou:
Why Adaptively Collected Data Have Negative Bias and How to Correct for It. AISTATS 2018: 1261-1269 - [c17]Amirata Ghorbani, James Y. Zou:
Embedding for Informative Missingness: Deep Learning With Incomplete Data. Allerton 2018: 437-445 - [c16]Abubakar Abid, James Y. Zou:
A Stochastic Expectation-Maximization Approach to Shuffled Linear Regression. Allerton 2018: 470-477 - [c15]Ruishan Liu, James Zou:
The Effects of Memory Replay in Reinforcement Learning. Allerton 2018: 478-485 - [c14]Abubakar Abid, James Y. Zou:
Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders. NeurIPS 2018: 10568-10578 - 2017
- [c13]Aditi Raghunathan, Gregory Valiant, James Zou:
Estimating the unseen from multiple populations. ICML 2017: 2855-2863 - [c12]Fei Xia, Martin J. Zhang, James Y. Zou, David Tse:
NeuralFDR: Learning Discovery Thresholds from Hypothesis Features. NIPS 2017: 1541-1550 - [c11]Shyam Upadhyay, Kai-Wei Chang, Matt Taddy, Adam Kalai, James Y. Zou:
Beyond Bilingual: Multi-sense Word Embeddings using Multilingual Context. Rep4NLP@ACL 2017: 101-110 - 2016
- [c10]Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, Adam Tauman Kalai:
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. NIPS 2016: 4349-4357 - 2015
- [c9]James Y. Zou, Reshef Meir, David C. Parkes:
Strategic Voting Behavior in Doodle Polls. CSCW 2015: 464-472 - [c8]James Y. Zou, Kamalika Chaudhuri, Adam Tauman Kalai:
Crowdsourcing Feature Discovery via Adaptively Chosen Comparisons. HCOMP 2015: 198-205 - [c7]Panos Toulis, David C. Parkes, Elery Pfeffer, James Y. Zou:
Incentive-Compatible Experimental Design. EC 2015: 285-302 - 2013
- [c6]James Y. Zou, Daniel J. Hsu, David C. Parkes, Ryan Prescott Adams:
Contrastive Learning Using Spectral Methods. NIPS 2013: 2238-2246 - 2012
- [c5]Swaprava Nath, Pankaj Dayama, Dinesh Garg, Y. Narahari, James Y. Zou:
Threats and Trade-Offs in Resource Critical Crowdsourcing Tasks Over Networks. AAAI 2012: 2447-2448 - [c4]Anders Johannson, James Y. Zou:
A Slime Mold Solver for Linear Programming Problems. CiE 2012: 344-354 - [c3]James Y. Zou, Ryan P. Adams:
Priors for Diversity in Generative Latent Variable Models. NIPS 2012: 3005-3013 - [c2]Swaprava Nath, Pankaj Dayama, Dinesh Garg, Yadati Narahari, James Y. Zou:
Mechanism Design for Time Critical and Cost Critical Task Execution via Crowdsourcing. WINE 2012: 212-226 - 2010
- [c1]James Y. Zou, Sujit Gujar, David C. Parkes:
Tolerable Manipulability in Dynamic Assignment without Money. AAAI 2010: 947-952
Informal and Other Publications
- 2024
- [i135]Haonan Wang, James Zou, Michael Mozer, Anirudh Goyal, Alex Lamb, Linjun Zhang, Weijie J. Su, Zhun Deng, Michael Qizhe Xie, Hannah Brown, Kenji Kawaguchi:
Can AI Be as Creative as Humans? CoRR abs/2401.01623 (2024) - [i134]Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao:
TrustLLM: Trustworthiness in Large Language Models. CoRR abs/2401.05561 (2024) - [i133]Xinyu Yang, Weixin Liang, James Zou:
Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on Hugging Face. CoRR abs/2401.13822 (2024) - [i132]Ian Covert, Chanwoo Kim, Su-In Lee, James Zou, Tatsunori Hashimoto:
Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attribution. CoRR abs/2401.15866 (2024) - [i131]Kevin Wu, Eric Wu, Ally Cassasola, Angela Zhang, Kevin Wei, Teresa Nguyen, Sith Riantawan, Patricia Shi Riantawan, Daniel E. Ho, James Zou:
How well do LLMs cite relevant medical references? An evaluation framework and analyses. CoRR abs/2402.02008 (2024) - [i130]Weixin Liang, Nazneen Rajani, Xinyu Yang, Ezinwanne Ozoani, Eric Wu, Yiqun Chen, Daniel Scott Smith, James Zou:
What's documented in AI? Systematic Analysis of 32K AI Model Cards. CoRR abs/2402.05160 (2024) - [i129]Federico Bianchi, Patrick John Chia, Mert Yüksekgönül, Jacopo Tagliabue, Dan Jurafsky, James Zou:
How Well Can LLMs Negotiate? NegotiationArena Platform and Analysis. CoRR abs/2402.05863 (2024) - [i128]Federico Bianchi, James Zou:
Large Language Models are Vulnerable to Bait-and-Switch Attacks for Generating Harmful Content. CoRR abs/2402.13926 (2024) - [i127]Lingjiao Chen, Jared Quincy Davis, Boris Hanin, Peter Bailis, Ion Stoica, Matei Zaharia, James Zou:
Are More LLM Calls All You Need? Towards Scaling Laws of Compound Inference Systems. CoRR abs/2403.02419 (2024) - [i126]Weixin Liang, Zachary Izzo, Yaohui Zhang, Haley Lepp, Hancheng Cao, Xuandong Zhao, Lingjiao Chen, Haotian Ye, Sheng Liu, Zhi Huang, Daniel A. McFarland, James Y. Zou:
Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews. CoRR abs/2403.07183 (2024) - 2023
- [i125]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) - [i124]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) - [i123]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) - [i122]Weixin Liang, Mert Yüksekgönül, Yining Mao, Eric Wu, James Zou:
GPT detectors are biased against non-native English writers. CoRR abs/2304.02819 (2023) - [i121]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) - [i120]Yongchan Kwon, James Zou:
Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value. CoRR abs/2304.07718 (2023) - [i119]Zachary Izzo, Ruishan Liu, James Zou:
Data-Driven Subgroup Identification for Linear Regression. CoRR abs/2305.00195 (2023) - [i118]Shirley Wu, Mert Yüksekgönül, Linjun Zhang, James Zou:
Discover and Cure: Concept-aware Mitigation of Spurious Correlation. CoRR abs/2305.00650 (2023) - [i117]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) - [i116]Lingjiao Chen, Matei Zaharia, James Zou:
FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance. CoRR abs/2305.05176 (2023) - [i115]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) - [i114]Mert Yüksekgönül, Linjun Zhang, James Zou, Carlos Guestrin:
Beyond Confidence: Reliable Models Should Also Consider Atypicality. CoRR abs/2305.18262 (2023) - [i113]Kailas Vodrahalli, James Zou:
ArtWhisperer: A Dataset for Characterizing Human-AI Interactions in Artistic Creations. CoRR abs/2306.08141 (2023) - [i112]Kevin Fu Jiang, Weixin Liang, James Zou, Yongchan Kwon:
OpenDataVal: a Unified Benchmark for Data Valuation. CoRR abs/2306.10577 (2023) - [i111]Xinming Tu, James Zou, Weijie J. Su, Linjun Zhang:
What Should Data Science Education Do with Large Language Models? CoRR abs/2307.02792 (2023) - [i110]Lingjiao Chen, Matei Zaharia, James Zou:
How is ChatGPT's behavior changing over time? CoRR abs/2307.09009 (2023) - [i109]Rong Ma, Eric D. Sun, David Donoho, James Zou:
Is your data alignable? Principled and interpretable alignability testing and integration of single-cell data. CoRR abs/2308.01839 (2023) - [i108]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) - [i107]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) - [i106]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) - [i105]Weixin Liang, Yuhui Zhang, Hancheng Cao, Binglu Wang, Daisy Ding, Xinyu Yang, Kailas Vodrahalli, Siyu He, Daniel Scott 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) - [i104]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) - [i103]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 M. 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) - [i102]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) - [i101]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) - [i100]Shirley Wu, Kaidi Cao, Bruno Ribeiro, James Zou, Jure Leskovec:
GraphMETRO: Mitigating Complex Distribution Shifts in GNNs via Mixture of Aligned Experts. CoRR abs/2312.04693 (2023) - [i99]Jiachen Zhao, Zhun Deng, David Madras, James Zou, Mengye Ren:
Learning and Forgetting Unsafe Examples in Large Language Models. CoRR abs/2312.12736 (2023) - 2022
- [i98]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) - [i97]Antonio Ginart, Laurens van der Maaten, James Zou, Chuan Guo:
Submix: Practical Private Prediction for Large-Scale Language Models. CoRR abs/2201.00971 (2022) - [i96]Yongchan Kwon, Antonio Ginart, James Zou:
Competition over data: how does data purchase affect users? CoRR abs/2201.10774 (2022) - [i95]Kailas Vodrahalli, Tobias Gerstenberg, James Zou:
Uncalibrated Models Can Improve Human-AI Collaboration. CoRR abs/2202.05983 (2022) - [i94]Weixin Liang, James Zou:
MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts. CoRR abs/2202.06523 (2022) - [i93]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) - [i92]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) - [i91]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) - [i90]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 V. 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) - [i89]Jaime Roquero Gimenez, James Y. Zou:
A Unified f-divergence Framework Generalizing VAE and GAN. CoRR abs/2205.05214 (2022) - [i88]Mert Yüksekgönül, Maggie Wang, James Zou:
Post-hoc Concept Bottleneck Models. CoRR abs/2205.15480 (2022) - [i87]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) - [i86]Zhiying Zhu, Weixin Liang, James Zou:
GSCLIP : A Framework for Explaining Distribution Shifts in Natural Language. CoRR abs/2206.15007 (2022) - [i85]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) - [i84]Lingjiao Chen, Matei Zaharia, James Zou:
Estimating and Explaining Model Performance When Both Covariates and Labels Shift. CoRR abs/2209.08436 (2022) - [i83]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) - [i82]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) - [i81]Yongchan Kwon, James Zou:
WeightedSHAP: analyzing and improving Shapley based feature attributions. CoRR abs/2209.13429 (2022) - [i80]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) - [i79]Xinyi Zhao, Weixin Liang, James Zou:
Data Budgeting for Machine Learning. CoRR abs/2210.00987 (2022) - [i78]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) - [i77]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) - [i76]Huaxiu Yao, Yiping Wang, Linjun Zhang, James Zou, Chelsea Finn:
C-Mixup: Improving Generalization in Regression. CoRR abs/2210.05775 (2022) - [i75]Nazneen Rajani, Weixin Liang, Lingjiao Chen, Meg Mitchell, James Zou:
SEAL : Interactive Tool for Systematic Error Analysis and Labeling. CoRR abs/2210.05839 (2022) - [i74]Haotian Ye, James Zou, Linjun Zhang:
Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise. CoRR abs/2210.11075 (2022) - [i73]Rong Ma, Eric D. Sun, James Zou:
A Spectral Method for Assessing and Combining Multiple Data Visualizations. CoRR abs/2210.13711 (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
- [i69]Abubakar Abid, Maheen Farooqi, James Zou:
Persistent Anti-Muslim Bias in Large Language Models. CoRR abs/2101.05783 (2021) - [i68]Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou:
When and How Mixup Improves Calibration. CoRR abs/2102.06289 (2021) - [i67]Zachary Izzo, Lexing Ying, James Zou:
How to Learn when Data Reacts to Your Model: Performative Gradient Descent. CoRR abs/2102.07698 (2021) - [i66]Lingjiao Chen, Matei Zaharia, James Zou:
FrugalMCT: Efficient Online ML API Selection for Multi-Label Classification Tasks. CoRR abs/2102.09127 (2021) - [i65]Amirata Ghorbani, James Zou, Andre Esteva:
Data Shapley Valuation for Efficient Batch Active Learning. CoRR abs/2104.08312 (2021) - [i64]Antonio Ginart, Martin Jinye Zhang, James Zou:
MLDemon: Deployment Monitoring for Machine Learning Systems. CoRR abs/2104.13621 (2021) - [i63]Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Zou:
Adversarial Training Helps Transfer Learning via Better Representations. CoRR abs/2106.10189 (2021) - [i62]Farzan Farnia, Amirali Aghazadeh, James Zou, David Tse:
Group-Structured Adversarial Training. CoRR abs/2106.10324 (2021) - [i61]Grant Duffy, Paul P. Cheng, Neal Yuan, Bryan He, Alan C. Kwan, Matthew J. Shun-Shin, Kevin M. Alexander, Joseph Ebinger, Matthew P. Lungren, Florian Rader, David H. Liang, Ingela Schnittger, Euan A. Ashley, James Y. Zou, Jignesh Patel, Ronald Witteles, Susan Cheng, David Ouyang:
High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy with Cardiovascular Deep Learning. CoRR abs/2106.12511 (2021) - [i60]Abubakar Abid, James Zou:
Meaningfully Explaining a Model's Mistakes. CoRR abs/2106.12723 (2021) - [i59]Kailas Vodrahalli, Tobias Gerstenberg, James Zou:
Do Humans Trust Advice More if it Comes from AI? An Analysis of Human-AI Interactions. CoRR abs/2107.07015 (2021) - [i58]Lingjiao Chen, Tracy Cai, Matei Zaharia, James Zou:
Did the Model Change? Efficiently Assessing Machine Learning API Shifts. CoRR abs/2107.14203 (2021) - [i57]Wenlong Ji, Zhun Deng, Ryumei Nakada, James Zou, Linjun Zhang:
The Power of Contrast for Feature Learning: A Theoretical Analysis. CoRR abs/2110.02473 (2021) - [i56]Tarek Naous, Srinjay Sarkar, Abubakar Abid, James Zou:
Clustering Plotted Data by Image Segmentation. CoRR abs/2110.05187 (2021) - [i55]Yongchan Kwon, James Zou:
Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning. CoRR abs/2110.14049 (2021) - [i54]Amirata Ghorbani, Dina Berenbaum, Maor Ivgi, Yuval Dafna, James Zou:
Beyond Importance Scores: Interpreting Tabular ML by Visualizing Feature Semantics. CoRR abs/2111.05898 (2021) - [i53]Roxana Daneshjou, Kailas Vodrahalli, Weixin Liang, Roberto A. Novoa, Melissa Jenkins, Veronica Rotemberg, Justin Ko, Susan M. Swetter, Elizabeth E. Bailey, Olivier Gevaert, Pritam Mukherjee, Michelle Phung, Kiana Yekrang, Bradley Fong, Rachna Sahasrabudhe, James Zou, Albert Chiou:
Disparities in Dermatology AI: Assessments Using Diverse Clinical Images. CoRR abs/2111.08006 (2021) - [i52]Eric Wu, Kevin Wu, James Zou:
Explaining medical AI performance disparities across sites with confounder Shapley value analysis. CoRR abs/2111.08168 (2021) - [i51]Zachary Izzo, James Zou, Lexing Ying:
How to Learn when Data Gradually Reacts to Your Model. CoRR abs/2112.07042 (2021) - 2020
- [i50]Amirata Ghorbani, James Y. Zou:
Neuron Shapley: Discovering the Responsible Neurons. CoRR abs/2002.09815 (2020) - [i49]Zachary Izzo, Mary Anne Smart, Kamalika Chaudhuri, James Y. Zou:
Approximate Data Deletion from Machine Learning Models: Algorithms and Evaluations. CoRR abs/2002.10077 (2020) - [i48]Amirata Ghorbani, Michael P. Kim, James Y. Zou:
A Distributional Framework for Data Valuation. CoRR abs/2002.12334 (2020) - [i47]Abubakar Abid, James Y. Zou:
Improving Training on Noisy Stuctured Labels. CoRR abs/2003.03862 (2020) - [i46]Weixin Liang, James Zou, Zhou Yu:
Beyond User Self-Reported Likert Scale Ratings: A Comparison Model for Automatic Dialog Evaluation. CoRR abs/2005.10716 (2020) - [i45]Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Zou, Sergey Levine, Chelsea Finn, Tengyu Ma:
MOPO: Model-based Offline Policy Optimization. CoRR abs/2005.13239 (2020) - [i44]Lingjiao Chen, Matei Zaharia, James Zou:
FrugalML: How to Use ML Prediction APIs More Accurately and Cheaply. CoRR abs/2006.07512 (2020) - [i43]Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Y. Zou:
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data. CoRR abs/2006.08476 (2020) - [i42]Yongchan Kwon, Manuel A. Rivas, James Zou:
Efficient computation and analysis of distributional Shapley values. CoRR abs/2007.01357 (2020) - [i41]Antonio Ginart, Eva Zhang, James Zou:
Competing AI: How competition feedback affects machine learning. CoRR abs/2009.06797 (2020) - [i40]Weixin Liang, James Zou, Zhou Yu:
ALICE: Active Learning with Contrastive Natural Language Explanations. CoRR abs/2009.10259 (2020) - [i39]Kailas Vodrahalli, Roxana Daneshjou, Roberto A. Novoa, Albert Chiou, Justin M. Ko, James Zou:
TrueImage: A Machine Learning Algorithm to Improve the Quality of Telehealth Photos. CoRR abs/2010.02086 (2020) - [i38]Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Y. Zou:
How Does Mixup Help With Robustness and Generalization? CoRR abs/2010.04819 (2020) - [i37]Siyi Tang, Amirata Ghorbani, Rikiya Yamashita, Sameer Rehman, Jared A. Dunnmon, James Y. Zou, Daniel L. Rubin:
Data Valuation for Medical Imaging Using Shapley Value: Application on A Large-scale Chest X-ray Dataset. CoRR abs/2010.08006 (2020) - [i36]Weixin Liang, James Zou:
Neural Group Testing to Accelerate Deep Learning. CoRR abs/2011.10704 (2020) - 2019
- [i35]Abubakar Abid, Muhammad Fatih Balin, James Y. Zou:
Concrete Autoencoders for Differentiable Feature Selection and Reconstruction. CoRR abs/1901.09346 (2019) - [i34]Martin J. Zhang, James Zou, David Tse:
Adaptive Monte Carlo Multiple Testing via Multi-Armed Bandits. CoRR abs/1902.00197 (2019) - [i33]Abubakar Abid, James Y. Zou:
Contrastive Variational Autoencoder Enhances Salient Features. CoRR abs/1902.04601 (2019) - [i32]Dorottya Demszky, Nikhil Garg, Rob Voigt, James Zou, Matthew Gentzkow, Jesse Shapiro, Dan Jurafsky:
Analyzing Polarization in Social Media: Method and Application to Tweets on 21 Mass Shootings. CoRR abs/1904.01596 (2019) - [i31]Amirata Ghorbani, James Y. Zou:
Data Shapley: Equitable Valuation of Data for Machine Learning. CoRR abs/1904.02868 (2019) - [i30]Jaime Roquero Gimenez, James Y. Zou:
Discovering Conditionally Salient Features with Statistical Guarantees. CoRR abs/1905.12177 (2019) - [i29]Abubakar Abid, Ali Abdalla, Ali Abid, Dawood Khan, Abdulrahman Alfozan, James Y. Zou:
Gradio: Hassle-Free Sharing and Testing of ML Models in the Wild. CoRR abs/1906.02569 (2019) - [i28]Antonio Ginart, Melody Y. Guan, Gregory Valiant, James Zou:
Making AI Forget You: Data Deletion in Machine Learning. CoRR abs/1907.05012 (2019) - [i27]Allen Nie, Arturo L. Pineda, Matt W. Wright, Hannah Wand, Bryan Wulf, Helio A. Costa, Ronak Y. Patel, Carlos D. Bustamante, James Zou:
LitGen: Genetic Literature Recommendation Guided by Human Explanations. CoRR abs/1909.10699 (2019) - [i26]Antonio Ginart, Maxim Naumov, Dheevatsa Mudigere, Jiyan Yang, James Zou:
Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems. CoRR abs/1909.11810 (2019) - [i25]Ruishan Liu, Akshay Balsubramani, James Zou:
Learning transport cost from subset correspondence. CoRR abs/1909.13203 (2019) - [i24]Gal Yona, Amirata Ghorbani, James Y. Zou:
Who's responsible? Jointly quantifying the contribution of the learning algorithm and training data. CoRR abs/1910.04214 (2019) - 2018
- [i23]Abubakar Abid, James Y. Zou:
Stochastic EM for Shuffled Linear Regression. CoRR abs/1804.00681 (2018) - [i22]Anvita Gupta, James Zou:
Feedback GAN (FBGAN) for DNA: a Novel Feedback-Loop Architecture for Optimizing Protein Functions. CoRR abs/1804.01694 (2018) - [i21]Michael P. Kim, Amirata Ghorbani, James Y. Zou:
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification. CoRR abs/1805.12317 (2018) - [i20]Allen Nie, Ashley Zehnder, Rodney López Page, Arturo L. Pineda, Manuel A. Rivas, Carlos D. Bustamante, James Zou:
DeepTag: inferring all-cause diagnoses from clinical notes in under-resourced medical domain. CoRR abs/1806.10722 (2018) - [i19]Jaime Roquero Gimenez, Amirata Ghorbani, James Y. Zou:
Knockoffs for the mass: new feature importance statistics with false discovery guarantees. CoRR abs/1807.06214 (2018) - [i18]Abubakar Abid, James Y. Zou:
Autowarp: Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders. CoRR abs/1810.10107 (2018) - [i17]Jaime Roquero Gimenez, James Y. Zou:
Improving the Stability of the Knockoff Procedure: Multiple Simultaneous Knockoffs and Entropy Maximization. CoRR abs/1810.11378 (2018) - [i16]Abdi-Hakin Dirie, Abubakar Abid, James Y. Zou:
Contrastive Multivariate Singular Spectrum Analysis. CoRR abs/1810.13317 (2018) - [i15]Yuhui Zhang, Allen Nie, James Zou:
Large-scale Generative Modeling to Improve Automated Veterinary Disease Coding. CoRR abs/1811.11958 (2018) - 2017
- [i14]Shyam Upadhyay, Kai-Wei Chang, Matt Taddy, Adam Tauman Kalai, James Y. Zou:
Beyond Bilingual: Multi-sense Word Embeddings using Multilingual Context. CoRR abs/1706.08160 (2017) - [i13]Aditi Raghunathan, Gregory Valiant, James Zou:
Estimating the unseen from multiple populations. CoRR abs/1707.03854 (2017) - [i12]Xinkun Nie, Xiaoying Tian, Jonathan Taylor, James Zou:
Why adaptively collected data have negative bias and how to correct for it. CoRR abs/1708.01977 (2017) - [i11]Abubakar Abid, Vivek Kumar Bagaria, Martin J. Zhang, James Y. Zou:
Contrastive Principal Component Analysis. CoRR abs/1709.06716 (2017) - [i10]Ruishan Liu, James Zou:
The Effects of Memory Replay in Reinforcement Learning. CoRR abs/1710.06574 (2017) - [i9]Amirata Ghorbani, Abubakar Abid, James Y. Zou:
Interpretation of Neural Networks is Fragile. CoRR abs/1710.10547 (2017) - [i8]Nikhil Garg, Londa Schiebinger, Dan Jurafsky, James Zou:
Word Embeddings Quantify 100 Years of Gender and Ethnic Stereotypes. CoRR abs/1711.08412 (2017) - 2016
- [i7]Akash Srivastava, James Y. Zou, Ryan P. Adams, Charles Sutton:
Clustering with a Reject Option: Interactive Clustering as Bayesian Prior Elicitation. CoRR abs/1602.06886 (2016) - [i6]Akash Srivastava, James Y. Zou, Ryan P. Adams, Charles Sutton:
Clustering with a Reject Option: Interactive Clustering as Bayesian Prior Elicitation. CoRR abs/1606.05896 (2016) - [i5]Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, Adam Tauman Kalai:
Quantifying and Reducing Stereotypes in Word Embeddings. CoRR abs/1606.06121 (2016) - [i4]Hongyao Ma, Reshef Meir, David C. Parkes, James Y. Zou:
Contingent Payment Mechanisms to Maximize Resource Utilization. CoRR abs/1607.06511 (2016) - [i3]Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, Adam Kalai:
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. CoRR abs/1607.06520 (2016) - 2015
- [i2]James Y. Zou, Kamalika Chaudhuri, Adam Tauman Kalai:
Crowdsourcing Feature Discovery via Adaptively Chosen Comparisons. CoRR abs/1504.00064 (2015) - 2012
- [i1]Swaprava Nath, Pankaj Dayama, Dinesh Garg, Y. Narahari, James Y. Zou:
Mechanism Design for Time Critical and Cost Critical Task Execution via Crowdsourcing. CoRR abs/1208.1676 (2012)
Coauthor Index
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