Zachary C. Lipton

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Charles ElkanProfessor of Computer Science, University of California, San DiegoVerified email at ucsd.edu
Anima AnandkumarCalifornia Institute of Technology and NVIDIAVerified email at caltech.edu
Kamyar AzizzadenesheliNvidiaVerified email at nvidia.com
Julian McAuleyProfessor, UC San DiegoVerified email at eng.ucsd.edu
David KaleSenior Machine Learning Scientist, NetflixVerified email at netflix.com
John BerkowitzIn-Q-Tel LabsVerified email at iqt.org
Alex SmolaAmazon Web ServicesVerified email at smola.org
Jianfeng GaoMicrosoft Research, RedmondVerified email at microsoft.com
Lihong Li (李力鸿)AmazonVerified email at amazon.com
Divyansh KaushikPhD Student at Language Technologies Institute, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Bhuwan DhingraAssistant Professor, Computer Science, Duke UniversityVerified email at cs.duke.edu
Li DengChief AI Officer, Citadel (former)Verified email at ieee.org
Tommaso FurlanelloThinking and studying by myself.Verified email at usc.edu
Danish PruthiCarnegie Mellon UniversityVerified email at cs.cmu.edu
Mu LiAmazonVerified email at amazon.com
Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon UVerified email at cs.cmu.edu
Jean KossaifiSenior Research Scientist at NVIDIAVerified email at nvidia.com
Aran KhannaReserved.ai, Harvard University, Amazon AIVerified email at arankhanna.com
Graham NeubigAssociate Professor of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Saurabh GargPhD Student, Machine Learning Department, Carnegie Mellon UniversityVerified email at andrew.cmu.edu

Zachary C. Lipton

Assistant Professor of Machine Learning at CMU

Verified email at cmu.edu - Homepage

Machine Learning Healthcare Technology & Society Natural Language Processing Robustness & Causality


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	3305*	2016
A critical review of recurrent neural networks for sequence learning ZC Lipton, J Berkowitz, C Elkan arXiv preprint arXiv:1506.00019, 2015	2328	2015
Learning to Diagnose with LSTM Recurrent Neural Networks ZC Lipton, DC Kale, C Elkan, R Wetzell International Conference on Learning Representations (ICLR), 2015	1113	2015
Born again neural networks T Furlanello, ZC Lipton, M Tschannen, L Itti, A Anandkumar International Conference on Machine Learning (ICML), 2018	667	2018
Dive into Deep Learning AJS Aston Zhang, Zachary C. Lipton, Mu Li pre-print, 2020	501*	2020
Stochastic activation pruning for robust adversarial defense GS Dhillon, K Azizzadenesheli, ZC Lipton, J Bernstein, J Kossaifi, ... International Conference on Learning Representations (ICLR), 2018	465	2018
Optimal thresholding of classifiers to maximize F1 measure ZC Lipton, C Elkan, B Naryanaswamy European Conference on Machine Learning (ECML), 225-239, 2014	395*	2014
Modeling Missing Data in Clinical Time Series with RNNs ZC Lipton, DC Kale, R Wetzel Machine Learning for Healthcare (MLHC), 2016	385*	2016
Deep Active Learning for Named Entity Recognition Y Shen, H Yun, ZC Lipton, Y Kronrod, A Anandkumar International Conference on Learning Representations (ICLR), 2018	361	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	286	2020
Detecting and Correcting for Label Shift with Black Box Predictors ZC Lipton, YX Wang, A Smola International Conference on Machine Learning (ICML), 2018	279	2018
Troubling Trends in Machine Learning Scholarship ZC Lipton, J Steinhardt Communications of the ACM 62 (6), 45-53, 2019	258*	2019
Differential privacy and machine learning: a survey and review Z Ji, ZC Lipton, C Elkan arXiv preprint arXiv:1412.7584, 2014	247	2014
What is the Effect of Importance Weighting in Deep Learning? J Byrd, Z Lipton International Conference on Machine Learning (ICML), 872-881, 2019	212	2019
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	203*	2018
Precise Recovery of Latent Vectors from Generative Adversarial Networks ZC Lipton, S Tripathi ICLR Workshop 2017, 2017	188	2017
How Much Reading Does Reading Comprehension Require? A Critical Investigation of Popular Benchmarks D Kaushik, ZC Lipton Empirical Methods in Natural Language Processing (EMNLP), 2018	185	2018
Combating Adversarial Misspellings with Robust Word Recognition D Pruthi, B Dhingra, ZC Lipton Association for Computational Linguistics (ACL), 2019	181	2019
Does mitigating ML’s impact disparity require treatment disparity? ZC Lipton, A Chouldechova, J McAuley Advances in Neural Information Processing Systems (NeurIPS), 2018	167*	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	159	2019

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