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ORCIDZachary C. Lipton
Zachary Chase Lipton
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- affiliation: Carnegie Mellon University, Machine Learning Department, Pittsburgh, PA, USA
- affiliation (PhD 2017): University of California, San Diego, CA, USA
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2020 – today
- 2024
[j12]Divyansh Kaushik, Zachary C. Lipton, Alex John London:
Resolving the Human-Subjects Status of ML's Crowdworkers. Commun. ACM 67(5): 52-59 (2024)- [j11]Divyansh Kaushik, Zachary C. Lipton, Alex John London:
Resolving the Human-subjects Status of Machine Learning's Crowdworkers: What ethical framework should govern the interaction of ML researchers and crowdworkers? ACM Queue 21(6): 101-127 (2024) - [c110]Sanjana Ramprasad, Elisa Ferracane, Zachary C. Lipton:
Analyzing LLM Behavior in Dialogue Summarization: Unveiling Circumstantial Hallucination Trends. ACL (1) 2024: 12549-12561 - [c109]Helen Zhou, Audrey Huang, Kamyar Azizzadenesheli, David Childers, Zachary C. Lipton:
Timing as an Action: Learning When to Observe and Act. AISTATS 2024: 3979-3987 - [c108]Yewon Byun, Dylan Sam, Michael Oberst
, Zachary C. Lipton, Bryan Wilder:
Auditing Fairness under Unobserved Confounding. AISTATS 2024: 4339-4347 - [c107]Nave Frost, Zachary C. Lipton, Yishay Mansour, Michal Moshkovitz:
Partially Interpretable Models with Guarantees on Coverage and Accuracy. ALT 2024: 590-613 - [c106]Evan Fellman, Jacob Tyo, Zachary C. Lipton:
The Future of Web Data Mining: Insights from Multimodal and Code-based Extraction Methods. CASE 2024: 1-5 - [c105]Sanjana Ramprasad, Kundan Krishna, Zachary C. Lipton, Byron C. Wallace:
Evaluating the Factuality of Zero-shot Summarizers Across Varied Domains. EACL (2) 2024: 50-59 - [c104]Jennifer Hsia, Danish Pruthi, Aarti Singh, Zachary C. Lipton:
Goodhart's Law Applies to NLP's Explanation Benchmarks. EACL (Findings) 2024: 1322-1335 - [c103]Nil-Jana Akpinar, Zachary C. Lipton, Alexandra Chouldechova:
The Impact of Differential Feature Under-reporting on Algorithmic Fairness. FAccT 2024: 1355-1382 - [c102]Rasool Fakoor, Jonas Mueller, Zachary Chase Lipton, Pratik Chaudhari, Alex Smola:
Time-Varying Propensity Score to Bridge the Gap between the Past and Present. ICLR 2024 - [c101]Pratyush Maini, Sachin Goyal, Zachary Chase Lipton, J. Zico Kolter, Aditi Raghunathan:
T-MARS: Improving Visual Representations by Circumventing Text Feature Learning. ICLR 2024 - [c100]Tom Yan, Ziyu Xu, Zachary Chase Lipton:
Foundations of Testing for Finite-Sample Causal Discovery. ICML 2024 - [i142]Pratyush Maini, Zhili Feng, Avi Schwarzschild, Zachary C. Lipton, J. Zico Kolter:
TOFU: A Task of Fictitious Unlearning for LLMs. CoRR abs/2401.06121 (2024) - [i141]Nil-Jana Akpinar, Zachary C. Lipton, Alexandra Chouldechova:
The Impact of Differential Feature Under-reporting on Algorithmic Fairness. CoRR abs/2401.08788 (2024) - [i140]Michael Feffer, Anusha Sinha, Zachary C. Lipton, Hoda Heidari:
Red-Teaming for Generative AI: Silver Bullet or Security Theater? CoRR abs/2401.15897 (2024) - [i139]Sanjana Ramprasad, Kundan Krishna, Zachary C. Lipton, Byron C. Wallace:
Evaluating the Factuality of Zero-shot Summarizers Across Varied Domains. CoRR abs/2402.03509 (2024) - [i138]Xinyu Li, Zachary C. Lipton, Liu Leqi:
Personalized Language Modeling from Personalized Human Feedback. CoRR abs/2402.05133 (2024) - [i137]Jacob Tyo, Zachary C. Lipton:
Contrastive Multiple Instance Learning for Weakly Supervised Person ReID. CoRR abs/2402.07685 (2024) - [i136]Jacob Tyo, Motolani Olarinre, Youngseog Chung, Zachary C. Lipton:
Beyond the Mud: Datasets and Benchmarks for Computer Vision in Off-Road Racing. CoRR abs/2402.08025 (2024) - [i135]Kundan Krishna, Sanjana Ramprasad, Prakhar Gupta, Byron C. Wallace, Zachary C. Lipton, Jeffrey P. Bigham:
GenAudit: Fixing Factual Errors in Language Model Outputs with Evidence. CoRR abs/2402.12566 (2024) - [i134]Yewon Byun, Dylan Sam, Michael Oberst, Zachary C. Lipton, Bryan Wilder:
Auditing Fairness under Unobserved Confounding. CoRR abs/2403.14713 (2024) - [i133]Sachin Goyal, Pratyush Maini, Zachary C. Lipton, Aditi Raghunathan, J. Zico Kolter:
Scaling Laws for Data Filtering - Data Curation cannot be Compute Agnostic. CoRR abs/2404.07177 (2024) - [i132]Rishabh Ranjan, Saurabh Garg, Mrigank Raman, Carlos Guestrin, Zachary Chase Lipton:
Post-Hoc Reversal: Are We Selecting Models Prematurely? CoRR abs/2404.07815 (2024) - [i131]Avi Schwarzschild, Zhili Feng, Pratyush Maini, Zachary C. Lipton, J. Zico Kolter:
Rethinking LLM Memorization through the Lens of Adversarial Compression. CoRR abs/2404.15146 (2024) - [i130]Sanjana Ramprasad, Elisa Ferracane, Zachary C. Lipton:
Analyzing LLM Behavior in Dialogue Summarization: Unveiling Circumstantial Hallucination Trends. CoRR abs/2406.03487 (2024) - [i129]Hua Shen, Tiffany Knearem, Reshmi Ghosh, Kenan Alkiek, Kundan Krishna, Yachuan Liu, Ziqiao Ma, Savvas Petridis, Yi-Hao Peng, Li Qiwei, Sushrita Rakshit, Chenglei Si, Yutong Xie, Jeffrey P. Bigham, Frank Bentley, Joyce Chai, Zachary C. Lipton, Qiaozhu Mei, Rada Mihalcea, Michael Terry, Diyi Yang, Meredith Ringel Morris, Paul Resnick, David Jurgens:
Towards Bidirectional Human-AI Alignment: A Systematic Review for Clarifications, Framework, and Future Directions. CoRR abs/2406.09264 (2024) - [i128]Sumukh K. Aithal, Pratyush Maini, Zachary C. Lipton, J. Zico Kolter:
Understanding Hallucinations in Diffusion Models through Mode Interpolation. CoRR abs/2406.09358 (2024) - [i127]Daniel P. Jeong, Zachary C. Lipton, Pradeep Ravikumar:
LLM-Select: Feature Selection with Large Language Models. CoRR abs/2407.02694 (2024) - 2023
- [j10]Yifan Zhang, Hanlin Zhang, Zachary Chase Lipton, Li Erran Li, Eric P. Xing:
Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation. Trans. Mach. Learn. Res. 2023 (2023) - [c99]Michael Feffer, Hoda Heidari, Zachary C. Lipton:
Moral Machine or Tyranny of the Majority? AAAI 2023: 5974-5982 - [c98]Kundan Krishna, Saurabh Garg, Jeffrey P. Bigham, Zachary C. Lipton:
Downstream Datasets Make Surprisingly Good Pretraining Corpora. ACL (1) 2023: 12207-12222 - [c97]Michael Feffer, Michael Skirpan, Zachary C. Lipton, Hoda Heidari:
From Preference Elicitation to Participatory ML: A Critical Survey & Guidelines for Future Research. AIES 2023: 38-48 - [c96]Helen Zhou, Sivaraman Balakrishnan, Zachary C. Lipton:
Domain Adaptation under Missingness Shift. AISTATS 2023: 9577-9606 - [c95]Liu Leqi, Giulio Zhou, Fatma Kilinç-Karzan, Zachary C. Lipton, Alan L. Montgomery:
A Field Test of Bandit Algorithms for Recommendations: Understanding the Validity of Assumptions on Human Preferences in Multi-armed Bandits. CHI 2023: 504:1-504:16 - [c94]Helen Zhou, Yuwen Chen, Zachary C. Lipton:
Evaluating Model Performance in Medical Datasets Over Time. CHIL 2023: 498-508 - [c93]Shantanu Gupta, David Childers, Zachary Chase Lipton:
Local Causal Discovery for Estimating Causal Effects. CLeaR 2023: 408-447 - [c92]Kundan Krishna, Prakhar Gupta, Sanjana Ramprasad, Byron C. Wallace, Jeffrey P. Bigham, Zachary C. Lipton:
USB: A Unified Summarization Benchmark Across Tasks and Domains. EMNLP (Findings) 2023: 8826-8845 - [c91]Mrigank Raman, Pratyush Maini, J. Zico Kolter, Zachary C. Lipton, Danish Pruthi:
Model-tuning Via Prompts Makes NLP Models Adversarially Robust. EMNLP 2023: 9266-9286 - [c90]Michael Feffer, Zachary C. Lipton, Chris Donahue:
DeepDrake ft. BTS-GAN and TayloRVC: An Exploratory Analysis of Musical Deepfakes and Hosting Platforms. HCMIR@ISMIR 2023 - [c89]Zachary Novack, Simran Kaur, Tanya Marwah, Saurabh Garg, Zachary Chase Lipton:
Disentangling the Mechanisms Behind Implicit Regularization in SGD. ICLR 2023 - [c88]Saurabh Garg, Nick Erickson, James Sharpnack, Alex Smola, Sivaraman Balakrishnan, Zachary Chase Lipton:
RLSbench: Domain Adaptation Under Relaxed Label Shift. ICML 2023: 10879-10928 - [c87]Pratyush Maini, Michael Curtis Mozer, Hanie Sedghi, Zachary Chase Lipton, J. Zico Kolter, Chiyuan Zhang:
Can Neural Network Memorization Be Localized? ICML 2023: 23536-23557 - [c86]Tanya Marwah, Zachary Chase Lipton, Jianfeng Lu, Andrej Risteski:
Neural Network Approximations of PDEs Beyond Linearity: A Representational Perspective. ICML 2023: 24139-24172 - [c85]Zachary Novack, Julian J. McAuley, Zachary Chase Lipton, Saurabh Garg:
CHiLS: Zero-Shot Image Classification with Hierarchical Label Sets. ICML 2023: 26342-26362 - [c84]Jacob Tyo, Bhuwan Dhingra, Zachary C. Lipton:
Valla: Standardizing and Benchmarking Authorship Attribution and Verification Through Empirical Evaluation and Comparative Analysis. IJCNLP (1) 2023: 649-660 - [c83]Zachary Chase Lipton:
Reliable deep learning in dynamic environments. Medical Imaging: Computer-Aided Diagnosis 2023 - [c82]Dheeraj Baby, Saurabh Garg, Tzu-Ching Yen, Sivaraman Balakrishnan, Zachary C. Lipton, Yu-Xiang Wang:
Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms. NeurIPS 2023 - [c81]Saurabh Garg, Amrith Setlur, Zachary C. Lipton, Sivaraman Balakrishnan, Virginia Smith, Aditi Raghunathan:
Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift. NeurIPS 2023 - [c80]Tanya Marwah, Ashwini Pokle, J. Zico Kolter, Zachary C. Lipton, Jianfeng Lu, Andrej Risteski:
Deep Equilibrium Based Neural Operators for Steady-State PDEs. NeurIPS 2023 - [c79]Shubhanshu Shekhar, Ziyu Xu, Zachary C. Lipton, Pierre J. Liang, Aaditya Ramdas:
Risk-limiting financial audits via weighted sampling without replacement. UAI 2023: 1932-1941 - [e2]Kaivalya Deshpande, Madalina Fiterau, Shalmali Joshi, Zachary C. Lipton, Rajesh Ranganath, Iñigo Urteaga, Serene Yeung:
Machine Learning for Healthcare Conference, MLHC 2023, 11-12 August 2023, New York, USA. Proceedings of Machine Learning Research 219, PMLR 2023 [contents] - [i126]Jacob Tyo, Zachary C. Lipton:
Meta-Learning Mini-Batch Risk Functionals. CoRR abs/2301.11724 (2023) - [i125]Zachary Novack, Saurabh Garg, Julian J. McAuley, Zachary C. Lipton:
CHiLS: Zero-Shot Image Classification with Hierarchical Label Sets. CoRR abs/2302.02551 (2023) - [i124]Saurabh Garg, Nick Erickson, James Sharpnack, Alex Smola, Sivaraman Balakrishnan, Zachary C. Lipton:
RLSbench: Domain Adaptation Under Relaxed Label Shift. CoRR abs/2302.03020 (2023) - [i123]Tom Yan, Shantanu Gupta, Zachary C. Lipton:
Discovering Optimal Scoring Mechanisms in Causal Strategic Prediction. CoRR abs/2302.06804 (2023) - [i122]Shantanu Gupta, David Childers, Zachary C. Lipton:
Local Causal Discovery for Estimating Causal Effects. CoRR abs/2302.08070 (2023) - [i121]Alex Mei, Michael Saxon, Shiyu Chang, Zachary C. Lipton, William Yang Wang:
Users are the North Star for AI Transparency. CoRR abs/2303.05500 (2023) - [i120]Mrigank Raman, Pratyush Maini, J. Zico Kolter, Zachary C. Lipton, Danish Pruthi:
Model-tuning Via Prompts Makes NLP Models Adversarially Robust. CoRR abs/2303.07320 (2023) - [i119]Liu Leqi, Giulio Zhou, Fatma Kilinç-Karzan, Zachary C. Lipton, Alan L. Montgomery:
A Field Test of Bandit Algorithms for Recommendations: Understanding the Validity of Assumptions on Human Preferences in Multi-armed Bandits. CoRR abs/2304.09088 (2023) - [i118]Shubhanshu Shekhar, Ziyu Xu, Zachary C. Lipton, Pierre J. Liang, Aaditya Ramdas:
Risk-limiting Financial Audits via Weighted Sampling without Replacement. CoRR abs/2305.06884 (2023) - [i117]Helen Zhou, Yuwen Chen, Zachary C. Lipton:
Evaluating Model Performance in Medical Datasets Over Time. CoRR abs/2305.13426 (2023) - [i116]Kundan Krishna, Prakhar Gupta, Sanjana Ramprasad, Byron C. Wallace, Jeffrey P. Bigham, Zachary C. Lipton:
USB: A Unified Summarization Benchmark Across Tasks and Domains. CoRR abs/2305.14296 (2023) - [i115]Dhananjay Ashok, Zachary C. Lipton:
PromptNER: Prompting For Named Entity Recognition. CoRR abs/2305.15444 (2023) - [i114]Michael Feffer, Hoda Heidari, Zachary C. Lipton:
Moral Machine or Tyranny of the Majority? CoRR abs/2305.17319 (2023) - [i113]Dheeraj Baby, Saurabh Garg, Tzu-Ching Yen, Sivaraman Balakrishnan, Zachary Chase Lipton, Yu-Xiang Wang:
Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms. CoRR abs/2305.19570 (2023) - [i112]Pratyush Maini, Sachin Goyal, Zachary C. Lipton, J. Zico Kolter, Aditi Raghunathan:
T-MARS: Improving Visual Representations by Circumventing Text Feature Learning. CoRR abs/2307.03132 (2023) - [i111]Pratyush Maini, Michael C. Mozer, Hanie Sedghi, Zachary C. Lipton, J. Zico Kolter, Chiyuan Zhang:
Can Neural Network Memorization Be Localized? CoRR abs/2307.09542 (2023) - [i110]Jennifer Hsia, Danish Pruthi, Aarti Singh, Zachary C. Lipton:
Goodhart's Law Applies to NLP's Explanation Benchmarks. CoRR abs/2308.14272 (2023) - [i109]Jacob Tyo, Motolani Olarinre, Youngseog Chung, Zachary C. Lipton:
MUDD: A New Re-Identification Dataset with Efficient Annotation for Off-Road Racers in Extreme Conditions. CoRR abs/2311.08488 (2023) - [i108]Jacob Tyo, Youngseog Chung, Motolani Olarinre, Zachary C. Lipton:
Reading Between the Mud: A Challenging Motorcycle Racer Number Dataset. CoRR abs/2311.09256 (2023) - [i107]Yuwen Chen, Helen Zhou, Zachary C. Lipton:
MoCo-Transfer: Investigating out-of-distribution contrastive learning for limited-data domains. CoRR abs/2311.09401 (2023) - [i106]Tanya Marwah, Ashwini Pokle, J. Zico Kolter, Zachary C. Lipton, Jianfeng Lu, Andrej Risteski:
Deep Equilibrium Based Neural Operators for Steady-State PDEs. CoRR abs/2312.00234 (2023) - [i105]Saurabh Garg, Amrith Setlur, Zachary Chase Lipton, Sivaraman Balakrishnan, Virginia Smith, Aditi Raghunathan:
Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift. CoRR abs/2312.03318 (2023) - [i104]Micah Goldblum, Anima Anandkumar, Richard G. Baraniuk, Tom Goldstein, Kyunghyun Cho, Zachary C. Lipton, Melanie Mitchell, Preetum Nakkiran, Max Welling, Andrew Gordon Wilson:
Perspectives on the State and Future of Deep Learning - 2023. CoRR abs/2312.09323 (2023) - 2022
- [j9]Danish Pruthi, Rachit Bansal, Bhuwan Dhingra, Livio Baldini Soares, Michael Collins, Zachary C. Lipton, Graham Neubig, William W. Cohen:
Evaluating Explanations: How Much Do Explanations from the Teacher Aid Students? Trans. Assoc. Comput. Linguistics 10: 359-375 (2022) - [c78]Siddhant Arora, Danish Pruthi, Norman M. Sadeh, William W. Cohen, Zachary C. Lipton, Graham Neubig:
Explain, Edit, and Understand: Rethinking User Study Design for Evaluating Model Explanations. AAAI 2022: 5277-5285 - [c77]Omer Ben-Porat, Lee Cohen, Liu Leqi, Zachary C. Lipton, Yishay Mansour:
Modeling Attrition in Recommender Systems with Departing Bandits. AAAI 2022: 6072-6079 - [c76]Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli:
Off-Policy Risk Assessment for Markov Decision Processes. AISTATS 2022: 5022-5050 - [c75]Helen Zhou, Cheng Cheng, Kelly J. Shields, Gursimran Kochhar, Tariq Cheema, Zachary C. Lipton, Jeremy C. Weiss:
Learning Clinical Concepts for Predicting Risk of Progression to Severe COVID-19. AMIA 2022 - [c74]Anurag Katakkar, Clay H. Yoo, Weiqin Wang, Zachary C. Lipton, Divyansh Kaushik:
Practical Benefits of Feature Feedback Under Distribution Shift. BlackboxNLP@EMNLP 2022: 346-355 - [c73]Riccardo Fogliato, Sina Fazelpour, Shantanu Gupta, Zachary C. Lipton, David Danks:
Homophily and Incentive Effects in Use of Algorithms. CogSci 2022 - [c72]Simran Kaur, Jeremy Cohen, Zachary Chase Lipton:
On the Maximum Hessian Eigenvalue and Generalization. ICBINB 2022: 51-65 - [c71]Saurabh Garg, Sivaraman Balakrishnan, Zachary Chase Lipton, Behnam Neyshabur, Hanie Sedghi:
Leveraging unlabeled data to predict out-of-distribution performance. ICLR 2022 - [c70]Liu Leqi, Audrey Huang, Zachary C. Lipton, Kamyar Azizzadenesheli:
Supervised Learning with General Risk Functionals. ICML 2022: 12570-12592 - [c69]Saurabh Garg, Sivaraman Balakrishnan, Zachary C. Lipton:
Domain Adaptation under Open Set Label Shift. NeurIPS 2022 - [c68]Pratyush Maini, Saurabh Garg, Zachary C. Lipton, J. Zico Kolter:
Characterizing Datapoints via Second-Split Forgetting. NeurIPS 2022 - [c67]Manley Roberts, Pranav Mani, Saurabh Garg, Zachary C. Lipton:
Unsupervised Learning under Latent Label Shift. NeurIPS 2022 - [e1]Zachary C. Lipton, Rajesh Ranganath, Mark P. Sendak, Michael W. Sjoding, Serena Yeung:
Proceedings of the Machine Learning for Healthcare Conference, MLHC 2022, 5-6 August 2022, Durham, NC, USA. Proceedings of Machine Learning Research 182, PMLR 2022 [contents] - [i103]Saurabh Garg, Sivaraman Balakrishnan, Zachary C. Lipton, Behnam Neyshabur, Hanie Sedghi:
Leveraging Unlabeled Data to Predict Out-of-Distribution Performance. CoRR abs/2201.04234 (2022) - [i102]Yi-Fan Zhang, Hanlin Zhang, Zachary C. Lipton, Li Erran Li, Eric P. Xing:
Can Transformers be Strong Treatment Effect Estimators? CoRR abs/2202.01336 (2022) - [i101]Omer Ben-Porat, Lee Cohen, Liu Leqi, Zachary C. Lipton, Yishay Mansour:
Modeling Attrition in Recommender Systems with Departing Bandits. CoRR abs/2203.13423 (2022) - [i100]Riccardo Fogliato, Sina Fazelpour, Shantanu Gupta, Zachary C. Lipton, David Danks:
Homophily and Incentive Effects in Use of Algorithms. CoRR abs/2205.09701 (2022) - [i99]Divyansh Kaushik, Zachary C. Lipton, Alex John London:
Resolving the Human Subjects Status of Machine Learning's Crowdworkers. CoRR abs/2206.04039 (2022) - [i98]Simran Kaur, Jeremy Cohen, Zachary C. Lipton:
On the Maximum Hessian Eigenvalue and Generalization. CoRR abs/2206.10654 (2022) - [i97]Liu Leqi, Audrey Huang, Zachary C. Lipton, Kamyar Azizzadenesheli:
Supervised Learning with General Risk Functionals. CoRR abs/2206.13648 (2022) - [i96]Saurabh Garg, Sivaraman Balakrishnan, Zachary C. Lipton:
Domain Adaptation under Open Set Label Shift. CoRR abs/2207.13048 (2022) - [i95]Manley Roberts, Pranav Mani, Saurabh Garg, Zachary C. Lipton:
Unsupervised Learning under Latent Label Shift. CoRR abs/2207.13179 (2022) - [i94]Helen Zhou, Cheng Cheng, Kelly J. Shields, Gursimran Kochhar, Tariq Cheema, Zachary C. Lipton, Jeremy C. Weiss:
Learning Clinical Concepts for Predicting Risk of Progression to Severe COVID-19. CoRR abs/2208.13126 (2022) - [i93]Jacob Tyo, Bhuwan Dhingra, Zachary C. Lipton:
On the State of the Art in Authorship Attribution and Authorship Verification. CoRR abs/2209.06869 (2022) - [i92]Audrey Huang, Liu Leqi, Zachary Chase Lipton, Kamyar Azizzadenesheli:
Off-Policy Risk Assessment in Markov Decision Processes. CoRR abs/2209.10444 (2022) - [i91]Kundan Krishna, Saurabh Garg, Jeffrey P. Bigham, Zachary C. Lipton:
Downstream Datasets Make Surprisingly Good Pretraining Corpora. CoRR abs/2209.14389 (2022) - [i90]Rasool Fakoor, Jonas Mueller, Zachary C. Lipton, Pratik Chaudhari, Alexander J. Smola:
Data drift correction via time-varying importance weight estimator. CoRR abs/2210.01422 (2022) - [i89]Tanya Marwah, Zachary C. Lipton, Jianfeng Lu, Andrej Risteski:
Neural Network Approximations of PDEs Beyond Linearity: Representational Perspective. CoRR abs/2210.12101 (2022) - [i88]Pratyush Maini, Saurabh Garg, Zachary C. Lipton, J. Zico Kolter:
Characterizing Datapoints via Second-Split Forgetting. CoRR abs/2210.15031 (2022) - [i87]Helen Zhou, Sivaraman Balakrishnan, Zachary C. Lipton:
Domain Adaptation under Missingness Shift. CoRR abs/2211.02093 (2022) - [i86]Helen Zhou, Yuwen Chen, Zachary C. Lipton:
Model Evaluation in Medical Datasets Over Time. CoRR abs/2211.07165 (2022) - [i85]Zachary Novack, Simran Kaur, Tanya Marwah, Saurabh Garg, Zachary C. Lipton:
Disentangling the Mechanisms Behind Implicit Regularization in SGD. CoRR abs/2211.15853 (2022) - 2021
- [j8]Liu Leqi, Dylan Hadfield-Menell, Zachary C. Lipton:
When curation becomes creation. Commun. ACM 64(12): 44-47 (2021) - [j7]Riccardo Fogliato, Alexandra Chouldechova, Zachary C. Lipton:
The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies. Proc. ACM Hum. Comput. Interact. 5(CSCW2): 428:1-428:24 (2021) - [j6]Liu Leqi, Dylan Hadfield-Menell, Zachary C. Lipton:
When Curation Becomes Creation: Algorithms, microcontent, and the vanishing distinction between platforms and creators. ACM Queue 19(3): 11-15 (2021) - [c66]Aashiq Muhamed, Liang Li, Xingjian Shi, Suri Yaddanapudi, Wayne Chi, Dylan Jackson, Rahul Suresh, Zachary C. Lipton, Alexander J. Smola:
Symbolic Music Generation with Transformer-GANs. AAAI 2021: 408-417 - [c65]Kundan Krishna, Sopan Khosla, Jeffrey P. Bigham, Zachary C. Lipton:
Generating SOAP Notes from Doctor-Patient Conversations Using Modular Summarization Techniques. ACL/IJCNLP (1) 2021: 4958-4972 - [c64]Divyansh Kaushik, Douwe Kiela, Zachary C. Lipton, Wen-tau Yih:
On the Efficacy of Adversarial Data Collection for Question Answering: Results from a Large-Scale Randomized Study. ACL/IJCNLP (1) 2021: 6618-6633 - [c63]Jessica Dai, Sina Fazelpour, Zachary C. Lipton:
Fair Machine Learning Under Partial Compliance. AIES 2021: 55-65 - [c62]Riccardo Fogliato, Alice Xiang, Zachary C. Lipton, Daniel Nagin, Alexandra Chouldechova:
On the Validity of Arrest as a Proxy for Offense: Race and the Likelihood of Arrest for Violent Crimes. AIES 2021: 100-111 - [c61]