Zachary C. Lipton
Zachary C. Lipton
Assistant Professor of Operations Research & Machine Learning at CMU
Verified email at cmu.edu - Homepage
Title
Cited by
Cited by
Year
The Mythos of Model Interpretability
ZC Lipton
Communications of the ACM (CACM) [Prev. ICML Workshop on Human …, 2016
15992016
A critical review of recurrent neural networks for sequence learning
ZC Lipton, J Berkowitz, C Elkan
arXiv preprint arXiv:1506.00019, 2015
13502015
Learning to Diagnose with LSTM Recurrent Neural Networks
ZC Lipton, DC Kale, C Elkan, R Wetzell
International Conference on Learning Representations (ICLR), 2015
7302015
Born again neural networks
T Furlanello, ZC Lipton, M Tschannen, L Itti, A Anandkumar
International Conference on Machine Learning (ICML), 2018
2622018
Modeling Missing Data in Clinical Time Series with RNNs
ZC Lipton, DC Kale, R Wetzel
Machine Learning for Healthcare (MLHC), 2016
231*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
2302018
Optimal thresholding of classifiers to maximize F1 measure
ZC Lipton, C Elkan, B Naryanaswamy
European Conference on Machine Learning (ECML), 225-239, 2014
2022014
Deep Active Learning for Named Entity Recognition
Y Shen, H Yun, ZC Lipton, Y Kronrod, A Anandkumar
International Conference on Learning Representations (ICLR), 2018
1562018
Differential privacy and machine learning: a survey and review
Z Ji, ZC Lipton, C Elkan
arXiv preprint arXiv:1412.7584, 2014
1362014
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
132*2018
Troubling Trends in Machine Learning Scholarship
ZC Lipton, J Steinhardt
Communications of the ACM 62 (6), 45-53, 2019
1282019
Precise Recovery of Latent Vectors from Generative Adversarial Networks
ZC Lipton, S Tripathi
ICLR Workshop 2017, 2017
952017
Dive into deep learning
A Zhang, ZC Lipton, M Li, AJ Smola
Unpublished Draft. Retrieved 19, 2019, 2019
88*2019
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
882018
Detecting and Correcting for Label Shift with Black Box Predictors
ZC Lipton, YX Wang, A Smola
International Conference on Machine Learning (ICML), 2018
802018
Does mitigating ML’s impact disparity require treatment disparity?
ZC Lipton, A Chouldechova, J McAuley
Advances in Neural Information Processing Systems (NeurIPS), 2018
77*2018
Semantically decomposing the latent spaces of generative adversarial networks
C Donahue, A Balsubramani, J McAuley, ZC Lipton
International Conference on Learning Representations (ICLR), 2018
772018
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
772016
Learning From Noisy Singly-labeled Data
A Khetan, ZC Lipton, A Anandkumar
International Conference on Learning Representations (ICLR), 2018
672018
Generative concatenative nets jointly learn to write and classify reviews
ZC Lipton, S Vikram, J McAuley
arXiv preprint arXiv:1511.03683, 2015
66*2015
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