James Y. Zou

Publication Activity (10 Years)

Years Active: 2010-2023
Publications (10 Years): 74

Top Topics

Salient Features

Computed Tomography Images

Top Venues

Publications

Kevin Fu Jiang, Weixin Liang, James Y. Zou, Yongchan Kwon
OpenDataVal: a Unified Benchmark for Data Valuation. NeurIPS (2023)
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)
Kevin E. Wu, James Y. Zou, Howard Chang
Machine learning modeling of RNA structures: methods, challenges and future perspectives. Briefings Bioinform. 24 (4) (2023)
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 (2023)
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)
Mert Yüksekgönül, Linjun Zhang, James Y. Zou, Carlos Guestrin
Beyond Confidence: Reliable Models Should Also Consider Atypicality. NeurIPS (2023)
Yiqun Chen, James Y. Zou
TWIGMA: A dataset of AI-Generated Images with Metadata From Twitter. NeurIPS (2023)
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)
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)
Lingjiao Chen, Matei Zaharia, James Y. Zou
Estimating and Explaining Model Performance When Both Covariates and Labels Shift. NeurIPS (2022)
Yongchan Kwon, James Y. Zou
WeightedSHAP: analyzing and improving Shapley based feature attributions. NeurIPS (2022)
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 (2022)
Kailas Vodrahalli, Tobias Gerstenberg, James Y. Zou
Uncalibrated Models Can Improve Human-AI Collaboration. NeurIPS (2022)
Amirata Ghorbani, Dina Berenbaum, Maor Ivgi, Yuval Dafna, James Y. Zou
Beyond Importance Scores: Interpreting Tabular ML by Visualizing Feature Semantics. Inf. 13 (1) (2022)
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 (2022)
Jaime Roquero Gimenez, James Y. Zou
A Unified f-divergence Framework Generalizing VAE and GAN. CoRR (2022)
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)
Huaxiu Yao, Yiping Wang, Linjun Zhang, James Y. Zou, Chelsea Finn
C-Mixup: Improving Generalization in Regression. NeurIPS (2022)
Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Y. Zou
Adversarial Training Helps Transfer Learning via Better Representations. NeurIPS (2021)
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 (2021)
Girmaw Abebe Tadesse, Celia Cintas, Roxana Daneshjou, Kush R. Varshney, Peter 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)
Lingjiao Chen, Matei Zaharia, James Y. Zou
FrugalML: How to use ML Prediction APIs more accurately and cheaply. NeurIPS (2020)
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 (2020)
Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Y. Zou
How Does Mixup Help With Robustness and Generalization? CoRR (2020)
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)
Abubakar Abid, James Y. Zou
Improving Training on Noisy Stuctured Labels. CoRR (2020)
Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Y. Zou
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data. CoRR (2020)
Amirata Ghorbani, James Y. Zou
Neuron Shapley: Discovering the Responsible Neurons. CoRR (2020)
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) (2020)
Amirata Ghorbani, Michael P. Kim, James Y. Zou
A Distributional Framework for Data Valuation. CoRR (2020)
Amirata Ghorbani, James Y. Zou
Neuron Shapley: Discovering the Responsible Neurons. NeurIPS (2020)
Zachary Izzo, Mary Anne Smart, Kamalika Chaudhuri, James Y. Zou
Approximate Data Deletion from Machine Learning Models: Algorithms and Evaluations. CoRR (2020)
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)
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 (2019)
Amirata Ghorbani, Abubakar Abid, James Y. Zou
Interpretation of Neural Networks Is Fragile. AAAI (2019)
Jaime Roquero Gimenez, James Y. Zou
Discovering Conditionally Salient Features with Statistical Guarantees. ICML (2019)
Jaime Roquero Gimenez, James Y. Zou
Discovering Conditionally Salient Features with Statistical Guarantees. CoRR (2019)
Muhammed Fatih Balin, Abubakar Abid, James Y. Zou
Concrete Autoencoders: Differentiable Feature Selection and Reconstruction. ICML (2019)
Hongyao Ma, Reshef Meir, David C. Parkes, James Y. Zou
Contingent Payment Mechanisms for Resource Utilization. AAMAS (2019)
Amirata Ghorbani, James Wexler, James Y. Zou, Been Kim
Towards Automatic Concept-based Explanations. NeurIPS (2019)
Jaime Roquero Gimenez, Amirata Ghorbani, James Y. Zou
Knockoffs for the Mass: New Feature Importance Statistics with False Discovery Guarantees. AISTATS (2019)
Abubakar Abid, James Y. Zou
Contrastive Variational Autoencoder Enhances Salient Features. CoRR (2019)
Abdi-Hakin Dirie, Abubakar Abid, James Y. Zou
Contrastive Multivariate Singular Spectrum Analysis. Allerton (2019)
Amirata Ghorbani, James Y. Zou
Data Shapley: Equitable Valuation of Data for Machine Learning. ICML (2019)
Abubakar Abid, Muhammad Fatih Balin, James Y. Zou
Concrete Autoencoders for Differentiable Feature Selection and Reconstruction. CoRR (2019)
Jaime Roquero Gimenez, James Y. Zou
Improving the Stability of the Knockoff Procedure: Multiple Simultaneous Knockoffs and Entropy Maximization. AISTATS (2019)
Amirata Ghorbani, James Y. Zou
Data Shapley: Equitable Valuation of Data for Machine Learning. CoRR (2019)
Michael P. Kim, Amirata Ghorbani, James Y. Zou
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification. AIES (2019)
Gal Yona, Amirata Ghorbani, James Y. Zou
Who's responsible? Jointly quantifying the contribution of the learning algorithm and training data. CoRR (2019)
Abubakar Abid, James Y. Zou
Stochastic EM for Shuffled Linear Regression. CoRR (2018)
Jaime Roquero Gimenez, James Y. Zou
Improving the Stability of the Knockoff Procedure: Multiple Simultaneous Knockoffs and Entropy Maximization. CoRR (2018)
Abubakar Abid, James Y. Zou
Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders. NeurIPS (2018)
Michael P. Kim, Amirata Ghorbani, James Y. Zou
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification. CoRR (2018)
Amirata Ghorbani, James Y. Zou
Embedding for Informative Missingness: Deep Learning With Incomplete Data. Allerton (2018)
Abubakar Abid, James Y. Zou
A Stochastic Expectation-Maximization Approach to Shuffled Linear Regression. Allerton (2018)
Abdi-Hakin Dirie, Abubakar Abid, James Y. Zou
Contrastive Multivariate Singular Spectrum Analysis. CoRR (2018)
Jaime Roquero Gimenez, Amirata Ghorbani, James Y. Zou
Knockoffs for the mass: new feature importance statistics with false discovery guarantees. CoRR (2018)
Abubakar Abid, James Y. Zou
Autowarp: Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders. CoRR (2018)
Shyam Upadhyay, Kai-Wei Chang, Matt Taddy, Adam Kalai, James Y. Zou
Beyond Bilingual: Multi-sense Word Embeddings using Multilingual Context. Rep4NLP@ACL (2017)
Abubakar Abid, Vivek Kumar Bagaria, Martin J. Zhang, James Y. Zou
Contrastive Principal Component Analysis. CoRR (2017)
Shyam Upadhyay, Kai-Wei Chang, Matt Taddy, Adam Tauman Kalai, James Y. Zou
Beyond Bilingual: Multi-sense Word Embeddings using Multilingual Context. CoRR (2017)
Amirata Ghorbani, Abubakar Abid, James Y. Zou
Interpretation of Neural Networks is Fragile. CoRR (2017)
Fei Xia, Martin J. Zhang, James Y. Zou, David Tse
NeuralFDR: Learning Discovery Thresholds from Hypothesis Features. NIPS (2017)
Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, Adam Tauman Kalai
Quantifying and Reducing Stereotypes in Word Embeddings. CoRR (2016)
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 (2016)
Akash Srivastava, James Y. Zou, Ryan P. Adams, Charles Sutton
Clustering with a Reject Option: Interactive Clustering as Bayesian Prior Elicitation. CoRR (2016)
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)
Akash Srivastava, James Y. Zou, Ryan P. Adams, Charles Sutton
Clustering with a Reject Option: Interactive Clustering as Bayesian Prior Elicitation. CoRR (2016)
Hongyao Ma, Reshef Meir, David C. Parkes, James Y. Zou
Contingent Payment Mechanisms to Maximize Resource Utilization. CoRR (2016)
James Y. Zou, Eran Halperin, Esteban Gonzàlez Burchard, Sriram Sankararaman
Inferring parental genomic ancestries using pooled semi-Markov processes. Bioinform. 31 (12) (2015)
James Y. Zou, Reshef Meir, David C. Parkes
Strategic Voting Behavior in Doodle Polls. CSCW (2015)
Panos Toulis, David C. Parkes, Elery Pfeffer, James Y. Zou
Incentive-Compatible Experimental Design. EC (2015)
James Y. Zou, Kamalika Chaudhuri, Adam Tauman Kalai
Crowdsourcing Feature Discovery via Adaptively Chosen Comparisons. CoRR (2015)
James Y. Zou, Kamalika Chaudhuri, Adam Tauman Kalai
Crowdsourcing Feature Discovery via Adaptively Chosen Comparisons. HCOMP (2015)
James Y. Zou, Daniel J. Hsu, David C. Parkes, Ryan Prescott Adams
Contrastive Learning Using Spectral Methods. NIPS (2013)
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)
James Y. Zou, Ryan P. Adams
Priors for Diversity in Generative Latent Variable Models. NIPS (2012)
Anders Johannson, James Y. Zou
A Slime Mold Solver for Linear Programming Problems. CiE (2012)
Swaprava Nath, Pankaj Dayama, Dinesh Garg, Y. Narahari, James Y. Zou
Mechanism Design for Time Critical and Cost Critical Task Execution via Crowdsourcing CoRR (2012)
Swaprava Nath, Pankaj Dayama, Dinesh Garg, Y. Narahari, James Y. Zou
Threats and Trade-Offs in Resource Critical Crowdsourcing Tasks Over Networks. AAAI (2012)
James Y. Zou, Sujit Gujar, David C. Parkes
Tolerable Manipulability in Dynamic Assignment without Money. AAAI (2010)