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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
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2020 – today
- 2022
[j14]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)- [j13]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) - [j12]Weixin Liang, Girmaw Abebe Tadesse, Daniel 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) - [j11]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) - [c66]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 - [c65]Tony Ginart, Martin Jinye Zhang, James Zou:
MLDemon: Deployment Monitoring for Machine Learning Systems. AISTATS 2022: 3962-3997 - [c64]Zachary Izzo, James Zou, Lexing Ying:
How to Learn when Data Gradually Reacts to Your Model. AISTATS 2022: 3998-4035 - [c63]Yongchan Kwon, James Zou:
Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning. AISTATS 2022: 8780-8802 - [c62]Tarek Naous, Srinjay Sarkar, Abubakar Abid, James Zou:
Clustering Plotted Data by Image Segmentation. CVPR 2022: 21467-21472 - [c61]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 - [c60]Lingjiao Chen, Matei Zaharia, James Zou:
How Did the Model Change? Efficiently Assessing Machine Learning API Shifts. ICLR 2022 - [c59]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 - [c58]Weixin Liang, James Zou:
MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts. ICLR 2022 - [c57]Abubakar Abid, Mert Yüksekgönül, James Zou:
Meaningfully debugging model mistakes using conceptual counterfactual explanations. ICML 2022: 66-88 - [c56]Lingjiao Chen, Matei Zaharia, James Zou:
Efficient Online ML API Selection for Multi-Label Classification Tasks. ICML 2022: 3716-3746 - [c55]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 - [c54]Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou:
When and How Mixup Improves Calibration. ICML 2022: 26135-26160 - [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
- [j10]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) - [j9]Abubakar Abid, Maheen Farooqi, James Zou:
Large language models associate Muslims with violence. Nat. Mach. Intell. 3(6): 461-463 (2021) - [c53]Abubakar Abid, Maheen Farooqi, James Zou:
Persistent Anti-Muslim Bias in Large Language Models. AIES 2021: 298-306 - [c52]Gal Yona, Amirata Ghorbani, James Zou:
Who's Responsible? Jointly Quantifying the Contribution of the Learning Algorithm and Data. AIES 2021: 1034-1041 - [c51]Yongchan Kwon, Manuel A. Rivas, James Zou:
Efficient Computation and Analysis of Distributional Shapley Values. AISTATS 2021: 793-801 - [c50]Tony Ginart, Eva Zhang, Yongchan Kwon, James Zou:
Competing AI: How does competition feedback affect machine learning? AISTATS 2021: 1693-1701 - [c49]Zachary Izzo, Mary Anne Smart, Kamalika Chaudhuri, James Zou:
Approximate Data Deletion from Machine Learning Models. AISTATS 2021: 2008-2016 - [c48]Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Zou:
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data. AISTATS 2021: 2845-2853 - [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 - [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
- [j8]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) - [j7]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) - [j6]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) - [j5]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) - [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 - [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)
2010 – 2019
- 2019
- [j4]Anvita Gupta, James Zou:
Feedback GAN for DNA optimizes protein functions. Nat. Mach. Intell. 1(2): 105-111 (2019) - [j3]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) - [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]