追蹤
Zachary C. Lipton
Zachary C. Lipton
Raj Reddy Associate Professor of Machine Learning @ Carnegie Mellon University; CTO + CSO @ Abridge
在 cmu.edu 的電子郵件地址已通過驗證 - 首頁
標題
引用次數
引用次數
年份
The Mythos of Model Interpretability
ZC Lipton
Communications of the ACM (CACM), 2016
6404*2016
A critical review of recurrent neural networks for sequence learning
ZC Lipton, J Berkowitz, C Elkan
arXiv preprint arXiv:1506.00019, 2015
37732015
Dive into Deep Learning
AJS Aston Zhang, Zachary C. Lipton, Mu Li
pre-print, 2020
1781*2020
Learning to Diagnose with LSTM Recurrent Neural Networks
ZC Lipton, DC Kale, C Elkan, R Wetzell
International Conference on Learning Representations (ICLR), 2015
15382015
Born again neural networks
T Furlanello, ZC Lipton, M Tschannen, L Itti, A Anandkumar
International Conference on Machine Learning (ICML), 2018
12522018
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
10032019
Stochastic activation pruning for robust adversarial defense
GS Dhillon, K Azizzadenesheli, ZC Lipton, J Bernstein, J Kossaifi, ...
International Conference on Learning Representations (ICLR), 2018
7142018
Detecting and Correcting for Label Shift with Black Box Predictors
ZC Lipton, YX Wang, A Smola
International Conference on Machine Learning (ICML), 2018
6432018
Learning the Difference that Makes a Difference with Counterfactually-Augmented Data
D Kaushik, E Hovy, ZC Lipton
International Conference on Learning Representations (ICLR), 2020
6352020
Deep Active Learning for Named Entity Recognition
Y Shen, H Yun, ZC Lipton, Y Kronrod, A Anandkumar
International Conference on Learning Representations (ICLR), 2018
5872018
Modeling Missing Data in Clinical Time Series with RNNs
ZC Lipton, DC Kale, R Wetzel
Machine Learning for Healthcare (MLHC), 2016
587*2016
What is the Effect of Importance Weighting in Deep Learning?
J Byrd, Z Lipton
International Conference on Machine Learning (ICML), 872-881, 2019
5842019
Optimal thresholding of classifiers to maximize F1 measure
ZC Lipton, C Elkan, B Naryanaswamy
European Conference on Machine Learning (ECML), 225-239, 2014
5582014
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
4252018
Differential privacy and machine learning: a survey and review
Z Ji, ZC Lipton, C Elkan
arXiv preprint arXiv:1412.7584, 2014
4052014
Troubling Trends in Machine Learning Scholarship
ZC Lipton, J Steinhardt
Communications of the ACM 62 (6), 45-53, 2019
398*2019
Combating Adversarial Misspellings with Robust Word Recognition
D Pruthi, B Dhingra, ZC Lipton
Association for Computational Linguistics (ACL), 2019
3572019
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
3422016
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
282*2018
Does mitigating ML’s impact disparity require treatment disparity?
ZC Lipton, A Chouldechova, J McAuley
Advances in Neural Information Processing Systems (NeurIPS), 2018
2802018
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