Zachary C. Lipton - Google Scholar Citations

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	All	Since 2015
Citations	5158	5147
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20152016201720182019202025 136 498 1310 2284 848

Co-authors

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
John BerkowitzIn-Q-Tel LabsVerified email at iqt.org
Julian McAuleyAssociate Professor, UC San DiegoVerified email at eng.ucsd.edu
David KaleSenior Machine Learning Scientist, NetflixVerified email at netflix.com
Jianfeng GaoMicrosoft Research, RedmondVerified email at microsoft.com
Lihong Li (李力鸿)Research Scientist, GoogleVerified email at google.com
Li DengChief AI Officer, CitadelVerified email at ieee.org
Kamyar AzizzadenesheliPostdoctoral fellow at CaltechVerified email at caltech.edu
Jean KossaifiNVIDIA and Imperial College LondonVerified email at imperial.ac.uk
Aran KhannaHarvard University, Amazon AIVerified email at arankhanna.com
Tommaso FurlanelloPhd Candidate, University of Southern CaliforniaVerified email at usc.edu
Balakrishnan NarayanaswamyAWS AI, AmazonVerified email at amazon.com
Faisal Ahmed, PhDSUNY Stony BrookVerified email at cs.stonybrook.edu
Subarna TripathiIntel LabsVerified email at ucsd.edu
Jacob SteinhardtStanford UniversityVerified email at cs.stanford.edu
Alex SmolaAmazon Web ServicesVerified email at smola.org
Laurent IttiProfessor of Computer Science, University of Southern CaliforniaVerified email at usc.edu
Xiujun LiComputer Science and Engineering, University of Washington, Microsoft ResearchVerified email at microsoft.com
Bhuwan DhingraLanguage Technologies Institute, Carnegie Mellon UniversityVerified email at andrew.cmu.edu

Zachary C. Lipton

Assistant Professor of Operations Research & 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) [Prev. ICML Workshop on Human …, 2016	1231	2016
A critical review of recurrent neural networks for sequence learning ZC Lipton, J Berkowitz, C Elkan arXiv preprint arXiv:1506.00019, 2015	1107	2015
Learning to Diagnose with LSTM Recurrent Neural Networks ZC Lipton, DC Kale, C Elkan, R Wetzell International Conference on Learning Representations (ICLR), 2015	624	2015
Modeling Missing Data in Clinical Time Series with RNNs ZC Lipton, DC Kale, R Wetzel Machine Learning for Healthcare (MLHC), 2016	196*	2016
Stochastic activation pruning for robust adversarial defense GS Dhillon, K Azizzadenesheli, ZC Lipton, J Bernstein, J Kossaifi, ... International Conference on Learning Representations (ICLR), 2018	171	2018
Optimal thresholding of classifiers to maximize F1 measure ZC Lipton, C Elkan, B Naryanaswamy European Conference on Machine Learning (ECML), 225-239, 2014	161	2014
Born again neural networks T Furlanello, ZC Lipton, M Tschannen, L Itti, A Anandkumar International Conference on Machine Learning (ICML), 2018	158	2018
Differential privacy and machine learning: a survey and review Z Ji, ZC Lipton, C Elkan arXiv preprint arXiv:1412.7584, 2014	111	2014
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	107*	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	103	2018
Troubling Trends in Machine Learning Scholarship ZC Lipton, J Steinhardt Communications of the ACM 62 (6), 45-53, 2019	98	2019
Precise Recovery of Latent Vectors from Generative Adversarial Networks ZC Lipton, S Tripathi ICLR Workshop 2017, 2017	81	2017
Semantically decomposing the latent spaces of generative adversarial networks C Donahue, A Balsubramani, J McAuley, ZC Lipton International Conference on Learning Representations (ICLR), 2018	61	2018
Does mitigating ML’s impact disparity require treatment disparity? ZC Lipton, A Chouldechova, J McAuley Advances in Neural Information Processing Systems (NIPS), 2018	60*	2018
A user simulator for task-completion dialogues X Li, ZC Lipton, B Dhingra, L Li, J Gao, YN Chen arXiv preprint arXiv:1612.05688, 2016	59	2016
Generative concatenative nets jointly learn to write and classify reviews ZC Lipton, S Vikram, J McAuley arXiv preprint arXiv:1511.03683, 2015	57*	2015
Detecting and Correcting for Label Shift with Black Box Predictors ZC Lipton, YX Wang, A Smola International Conference on Machine Learning (ICML), 2018	52	2018
Learning From Noisy Singly-labeled Data A Khetan, ZC Lipton, A Anandkumar International Conference on Learning Representations (ICLR), 2018	49	2018
Combating Deep Reinforcement Learning's Sisyphean Curse with Intrinsic Fear ZC Lipton, J Gao, L Li, J Chen, L Deng	48*	2016
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	48	2016

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