Zachary C. Lipton

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Aston ZhangLlama team, MetaVerified email at meta.com
Anima AnandkumarCalifornia Institute of Technology and NVIDIAVerified email at caltech.edu
Alex SmolaBoson AIVerified email at smola.org
Kamyar AzizzadenesheliNvidiaVerified email at nvidia.com
Saurabh GargMistral AI | Past: CMU ML PhDVerified email at andrew.cmu.edu
Julian McAuleyProfessor, UC San DiegoVerified email at eng.ucsd.edu
Charles ElkanProfessor of Computer Science, University of California, San DiegoVerified email at ucsd.edu
Divyansh KaushikVice President, Beacon Global StrategiesVerified email at bgsdc.com
Mu LiAmazonVerified email at amazon.com
Sivaraman BalakrishnanCarnegie Mellon UniversityVerified email at stat.cmu.edu
Bhuwan DhingraAssistant Professor, Computer Science, Duke UniversityVerified email at cs.duke.edu
Jianfeng GaoMicrosoft Research, RedmondVerified email at microsoft.com
Lihong Li (李力鸿)AmazonVerified email at amazon.com
Danish PruthiIndian Institute of Science, BangaloreVerified email at iisc.ac.in
Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon UVerified email at cs.cmu.edu
John BerkowitzAppleVerified email at apple.com
Tommaso FurlanelloLeading Science at HK3 LabVerified email at usc.edu
Liu LeqiUT AustinVerified email at princeton.edu
Dave KaleData Science Manager, LiteratiVerified email at literati.com
Aran KhannaArchera.ai, Harvard University, Amazon AIVerified email at arankhanna.com

Zachary C. Lipton

Raj Reddy Associate Professor of Machine Learning @ Carnegie Mellon University; CTO + CSO @ Abridge

Verified email at cmu.edu - Homepage

Machine Learning Healthcare Technology & Society NLP Robustness & Adaptivity


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
The Mythos of Model Interpretability ZC Lipton Communications of the ACM (CACM), 2016	5865*	2016
A Critical Review of Recurrent Neural Networks for Sequence Learning ZC Lipton arXiv Preprint, CoRR, abs/1506.00019, 2015	3566*	2015
Dive into Deep Learning AJS Aston Zhang, Zachary C. Lipton, Mu Li pre-print, 2020	1570*	2020
Learning to Diagnose with LSTM Recurrent Neural Networks ZC Lipton, DC Kale, C Elkan, R Wetzell International Conference on Learning Representations (ICLR), 2015	1466	2015
Born again neural networks T Furlanello, ZC Lipton, M Tschannen, L Itti, A Anandkumar International Conference on Machine Learning (ICML), 2018	1190	2018
Learning robust global representations by penalizing local predictive power H Wang, S Ge, EP Xing, ZC Lipton Advances in Neural Information Processing Systems (NeurIPS), 2019	850	2019
Optimal thresholding of classifiers to maximize F1 measure ZC Lipton, C Elkan, B Naryanaswamy European Conference on Machine Learning (ECML), 225-239, 2014	719	2014
Stochastic activation pruning for robust adversarial defense GS Dhillon, K Azizzadenesheli, ZC Lipton, J Bernstein, J Kossaifi, ... International Conference on Learning Representations (ICLR), 2018	696	2018
Learning the Difference that Makes a Difference with Counterfactually-Augmented Data D Kaushik, E Hovy, ZC Lipton International Conference on Learning Representations (ICLR), 2020	608	2020
Detecting and Correcting for Label Shift with Black Box Predictors ZC Lipton, YX Wang, A Smola International Conference on Machine Learning (ICML), 2018	596	2018
Deep Active Learning for Named Entity Recognition Y Shen, H Yun, ZC Lipton, Y Kronrod, A Anandkumar International Conference on Learning Representations (ICLR), 2018	565	2018
Modeling Missing Data in Clinical Time Series with RNNs ZC Lipton, DC Kale, R Wetzel Machine Learning for Healthcare (MLHC), 2016	560*	2016
What is the Effect of Importance Weighting in Deep Learning? J Byrd, Z Lipton International Conference on Machine Learning (ICML), 872-881, 2019	527	2019
Failing loudly: An empirical study of methods for detecting dataset shift S Rabanser, S Günnemann, ZC Lipton Advances in Neural Information Processing Systems (NeurIPS), 2018	390	2018
Troubling Trends in Machine Learning Scholarship ZC Lipton, J Steinhardt Communications of the ACM 62 (6), 45-53, 2019	378*	2019
Differential privacy and machine learning: a survey and review Z Ji, ZC Lipton, C Elkan arXiv preprint arXiv:1412.7584, 2014	373	2014
Combating Adversarial Misspellings with Robust Word Recognition D Pruthi, B Dhingra, ZC Lipton Association for Computational Linguistics (ACL), 2019	337	2019
Context Matters: Refining Object Detection in Video with Recurrent Neural Networks S Tripathi, ZC Lipton, S Belongie, T Nguyen British Machine Vision Conference (BMVC), 2016	337	2016
Efficient exploration for dialogue policy learning with BBQ-networks ZC Lipton, J Gao, L Li, X Li, F Ahmed, L Deng Association for the Advancement of Artificial Intelligence (AAAI), 2018	274*	2018
Does mitigating ML’s impact disparity require treatment disparity? ZC Lipton, A Chouldechova, J McAuley Advances in Neural Information Processing Systems (NeurIPS), 2018	269	2018

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