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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
[j8]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)- [c57]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 - [c56]Tony Ginart, Martin Jinye Zhang, James Zou:
MLDemon: Deployment Monitoring for Machine Learning Systems. AISTATS 2022: 3962-3997 - [c55]Zachary Izzo, James Zou, Lexing Ying:
How to Learn when Data Gradually Reacts to Your Model. AISTATS 2022: 3998-4035 - [c54]Yongchan Kwon, James Zou:
Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning. AISTATS 2022: 8780-8802 - [c53]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 - [c52]Abubakar Abid, Mert Yüksekgönül, James Zou:
Meaningfully debugging model mistakes using conceptual counterfactual explanations. ICML 2022: 66-88 - [c51]Lingjiao Chen, Matei Zaharia, James Zou:
Efficient Online ML API Selection for Multi-Label Classification Tasks. ICML 2022: 3716-3746 - [c50]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 - [c49]Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou:
When and How Mixup Improves Calibration. ICML 2022: 26135-26160 - [i75]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) - [i74]Antonio Ginart, Laurens van der Maaten, James Zou, Chuan Guo:
Submix: Practical Private Prediction for Large-Scale Language Models. CoRR abs/2201.00971 (2022) - [i73]Yongchan Kwon, Antonio Ginart, James Zou:
Competition over data: how does data purchase affect users? CoRR abs/2201.10774 (2022) - [i72]Kailas Vodrahalli, Tobias Gerstenberg, James Zou:
Uncalibrated Models Can Improve Human-AI Collaboration. CoRR abs/2202.05983 (2022) - [i71]Weixin Liang, James Zou:
MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts. CoRR abs/2202.06523 (2022) - [i70]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) - [i69]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) - [i68]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) - [i67]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) - [i66]Jaime Roquero Gimenez, James Y. Zou:
A Unified f-divergence Framework Generalizing VAE and GAN. CoRR abs/2205.05214 (2022) - [i65]Mert Yüksekgönül, Maggie Wang, James Zou:
Post-hoc Concept Bottleneck Models. CoRR abs/2205.15480 (2022) - [i64]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) - [i63]Zhiying Zhu, Weixin Liang, James Zou:
GSCLIP : A Framework for Explaining Distribution Shifts in Natural Language. CoRR abs/2206.15007 (2022) - 2021
- [j7]Abubakar Abid, Maheen Farooqi, James Zou:
Large language models associate Muslims with violence. Nat. Mach. Intell. 3(6): 461-463 (2021) - [c48]Abubakar Abid, Maheen Farooqi, James Zou:
Persistent Anti-Muslim Bias in Large Language Models. AIES 2021: 298-306 - [c47]Gal Yona, Amirata Ghorbani, James Zou:
Who's Responsible? Jointly Quantifying the Contribution of the Learning Algorithm and Data. AIES 2021: 1034-1041 - [c46]Yongchan Kwon, Manuel A. Rivas, James Zou:
Efficient Computation and Analysis of Distributional Shapley Values. AISTATS 2021: 793-801 - [c45]Tony Ginart, Eva Zhang, Yongchan Kwon, James Zou:
Competing AI: How does competition feedback affect machine learning? AISTATS 2021: 1693-1701 - [c44]Zachary Izzo, Mary Anne Smart, Kamalika Chaudhuri, James Zou:
Approximate Data Deletion from Machine Learning Models. AISTATS 2021: 2008-2016 - [c43]Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Zou:
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data. AISTATS 2021: 2845-2853 - [c42]Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Zou:
How Does Mixup Help With Robustness and Generalization? ICLR 2021 - [c41]Zachary Izzo, Lexing Ying, James Zou:
How to Learn when Data Reacts to Your Model: Performative Gradient Descent. ICML 2021: 4641-4650 - [c40]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 - [c39]Weixin Liang, James Zou:
Neural Group Testing to Accelerate Deep Learning. ISIT 2021: 958-963 - [c38]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 - [c37]Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Y. Zou:
Adversarial Training Helps Transfer Learning via Better Representations. NeurIPS 2021: 25179-25191 - [c36]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 - [i62]Abubakar Abid, Maheen Farooqi, James Zou:
Persistent Anti-Muslim Bias in Large Language Models. CoRR abs/2101.05783 (2021) - [i61]Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou:
When and How Mixup Improves Calibration. CoRR abs/2102.06289 (2021) - [i60]Zachary Izzo, Lexing Ying, James Zou:
How to Learn when Data Reacts to Your Model: Performative Gradient Descent. CoRR abs/2102.07698 (2021) - [i59]Lingjiao Chen, Matei Zaharia, James Zou:
FrugalMCT: Efficient Online ML API Selection for Multi-Label Classification Tasks. CoRR abs/2102.09127 (2021) - [i58]Amirata Ghorbani, James Zou, Andre Esteva:
Data Shapley Valuation for Efficient Batch Active Learning. CoRR abs/2104.08312 (2021) - [i57]Antonio Ginart, Martin Jinye Zhang, James Zou:
MLDemon: Deployment Monitoring for Machine Learning Systems. CoRR abs/2104.13621 (2021) - [i56]Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Zou:
Adversarial Training Helps Transfer Learning via Better Representations. CoRR abs/2106.10189 (2021) - [i55]Farzan Farnia, Amirali Aghazadeh, James Zou, David Tse:
Group-Structured Adversarial Training. CoRR abs/2106.10324 (2021) - [i54]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) - [i53]Abubakar Abid, James Zou:
Meaningfully Explaining a Model's Mistakes. CoRR abs/2106.12723 (2021) - [i52]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) - [i51]Lingjiao Chen, Tracy Cai, Matei Zaharia, James Zou:
Did the Model Change? Efficiently Assessing Machine Learning API Shifts. CoRR abs/2107.14203 (2021) - [i50]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) - [i49]Tarek Naous, Srinjay Sarkar, Abubakar Abid, James Zou:
Clustering Plotted Data by Image Segmentation. CoRR abs/2110.05187 (2021) - [i48]Yongchan Kwon, James Zou:
Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning. CoRR abs/2110.14049 (2021) - [i47]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) - [i46]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) - [i45]Eric Wu, Kevin Wu, James Zou:
Explaining medical AI performance disparities across sites with confounder Shapley value analysis. CoRR abs/2111.08168 (2021) - [i44]Zachary Izzo, James Zou, Lexing Ying:
How to Learn when Data Gradually Reacts to Your Model. CoRR abs/2112.07042 (2021) - 2020
- [j6]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) - [j5]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) - [j4]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) - [c35]Weixin Liang, James Zou, Zhou Yu:
Beyond User Self-Reported Likert Scale Ratings: A Comparison Model for Automatic Dialog Evaluation. ACL 2020: 1363-1374 - [c34]Weixin Liang, James Zou, Zhou Yu:
ALICE: Active Learning with Contrastive Natural Language Explanations. EMNLP (1) 2020: 4380-4391 - [c33]Amirata Ghorbani, Michael P. Kim, James Zou:
A Distributional Framework For Data Valuation. ICML 2020: 3535-3544 - [c32]Lingjiao Chen, Matei Zaharia, James Y. Zou:
FrugalML: How to use ML Prediction APIs more accurately and cheaply. NeurIPS 2020 - [c31]Amirata Ghorbani, James Y. Zou:
Neuron Shapley: Discovering the Responsible Neurons. NeurIPS 2020 - [c30]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 - [i43]Amirata Ghorbani, James Y. Zou:
Neuron Shapley: Discovering the Responsible Neurons. CoRR abs/2002.09815 (2020) - [i42]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) - [i41]Amirata Ghorbani, Michael P. Kim, James Y. Zou:
A Distributional Framework for Data Valuation. CoRR abs/2002.12334 (2020) - [i40]Abubakar Abid, James Y. Zou:
Improving Training on Noisy Stuctured Labels. CoRR abs/2003.03862 (2020) - [i39]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) - [i38]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) - [i37]Lingjiao Chen, Matei Zaharia, James Zou:
FrugalML: How to Use ML Prediction APIs More Accurately and Cheaply. CoRR abs/2006.07512 (2020) - [i36]Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Y. Zou:
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data. CoRR abs/2006.08476 (2020) - [i35]Yongchan Kwon, Manuel A. Rivas, James Zou:
Efficient computation and analysis of distributional Shapley values. CoRR abs/2007.01357 (2020) - [i34]Antonio Ginart, Eva Zhang, James Zou:
Competing AI: How competition feedback affects machine learning. CoRR abs/2009.06797 (2020) - [i33]Weixin Liang, James Zou, Zhou Yu:
ALICE: Active Learning with Contrastive Natural Language Explanations. CoRR abs/2009.10259 (2020) - [i32]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) - [i31]Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Y. Zou:
How Does Mixup Help With Robustness and Generalization? CoRR abs/2010.04819 (2020) - [i30]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) - [i29]Weixin Liang, James Zou:
Neural Group Testing to Accelerate Deep Learning. CoRR abs/2011.10704 (2020)
2010 – 2019
- 2019
- [j3]Anvita Gupta, James Zou:
Feedback GAN for DNA optimizes protein functions. Nat. Mach. Intell. 1(2): 105-111 (2019) - [c29]Amirata Ghorbani, Abubakar Abid, James Y. Zou:
Interpretation of Neural Networks Is Fragile. AAAI 2019: 3681-3688 - [c28]Michael P. Kim, Amirata Ghorbani, James Y. Zou:
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification. AIES 2019: 247-254 - [c27]Jaime Roquero Gimenez, Amirata Ghorbani, James Y. Zou:
Knockoffs for the Mass: New Feature Importance Statistics with False Discovery Guarantees. AISTATS 2019: 2125-2133 - [c26]Jaime Roquero Gimenez, James Y. Zou:
Improving the Stability of the Knockoff Procedure: Multiple Simultaneous Knockoffs and Entropy Maximization. AISTATS 2019: 2184-2192 - [c25]Abdi-Hakin Dirie, Abubakar Abid, James Y. Zou:
Contrastive Multivariate Singular Spectrum Analysis. Allerton 2019: 1122-1127 - [c24]Hongyao Ma, Reshef Meir, David C. Parkes, James Y. Zou:
Contingent Payment Mechanisms for Resource Utilization. AAMAS 2019: 422-430 - [c23]Muhammed Fatih Balin, Abubakar Abid, James Y. Zou:
Concrete Autoencoders: Differentiable Feature Selection and Reconstruction. ICML 2019: 444-453 - [c22]Amirata Ghorbani, James Y. Zou:
Data Shapley: Equitable Valuation of Data for Machine Learning. ICML 2019: 2242-2251 - [c21]Jaime Roquero Gimenez, James Y. Zou:
Discovering Conditionally Salient Features with Statistical Guarantees. ICML 2019: 2290-2298 - [c20]Martin J. Zhang, James Zou, David Tse:
Adaptive Monte Carlo Multiple Testing via Multi-Armed Bandits. ICML 2019: 7512-7522 - [c19]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 - [c18]Antonio Ginart, Melody Y. Guan, Gregory Valiant, James Zou:
Making AI Forget You: Data Deletion in Machine Learning. NeurIPS 2019: 3513-3526 - [c17]Amirata Ghorbani, James Wexler, James Y. Zou, Been Kim:
Towards Automatic Concept-based Explanations. NeurIPS 2019: 9273-9282 - [c16]Martin J. Zhang, Fei Xia, James Zou:
AdaFDR: A Fast, Powerful and Covariate-Adaptive Approach to Multiple Hypothesis Testing. RECOMB 2019: 330-333 - [i28]Abubakar Abid, Muhammad Fatih Balin, James Y. Zou:
Concrete Autoencoders for Differentiable Feature Selection and Reconstruction. CoRR abs/1901.09346 (2019) - [i27]Martin J. Zhang, James Zou, David Tse:
Adaptive Monte Carlo Multiple Testing via Multi-Armed Bandits. CoRR abs/1902.00197 (2019) - [i26]Abubakar Abid, James Y. Zou:
Contrastive Variational Autoencoder Enhances Salient Features. CoRR abs/1902.04601 (2019) - [i25]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) - [i24]Amirata Ghorbani, James Y. Zou:
Data Shapley: Equitable Valuation of Data for Machine Learning. CoRR abs/1904.02868 (2019) - [i23]Jaime Roquero Gimenez, James Y. Zou:
Discovering Conditionally Salient Features with Statistical Guarantees. CoRR abs/1905.12177 (2019) - [i22]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) - [i21]Antonio Ginart, Melody Y. Guan, Gregory Valiant, James Zou:
Making AI Forget You: Data Deletion in Machine Learning. CoRR abs/1907.05012 (2019) - [i20]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) - [i19]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
- [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) - [c15]Amirata Ghorbani, James Y. Zou:
Embedding for Informative Missingness: Deep Learning With Incomplete Data. Allerton 2018: 437-445 - [c14]Abubakar Abid, James Y. Zou:
A Stochastic Expectation-Maximization Approach to Shuffled Linear Regression. Allerton 2018: 470-477 - [c13]Abubakar Abid, James Y. Zou:
Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders. NeurIPS 2018: 10568-10578 - [i18]Abubakar Abid, James Y. Zou:
Stochastic EM for Shuffled Linear Regression. CoRR abs/1804.00681 (2018) - [i17]Anvita Gupta, James Zou:
Feedback GAN (FBGAN) for DNA: a Novel Feedback-Loop Architecture for Optimizing Protein Functions. CoRR abs/1804.01694 (2018) - [i16]Michael P. Kim, Amirata Ghorbani, James Y. Zou:
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification. CoRR abs/1805.12317 (2018) - [i15]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) - [i14]Abubakar Abid, James Y. Zou:
Autowarp: Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders. CoRR abs/1810.10107 (2018) - [i13]Jaime Roquero Gimenez, James Y. Zou:
Improving the Stability of the Knockoff Procedure: Multiple Simultaneous Knockoffs and Entropy Maximization. CoRR abs/1810.11378 (2018) - [i12]Abdi-Hakin Dirie, Abubakar Abid, James Y. Zou:
Contrastive Multivariate Singular Spectrum Analysis. CoRR abs/1810.13317 (2018) - 2017
- [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 - [i11]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) - [i10]Abubakar Abid, Vivek Kumar Bagaria, Martin J. Zhang, James Y. Zou:
Contrastive Principal Component Analysis. CoRR abs/1709.06716 (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
- [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 - [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]