Zachary C. Lipton

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Aston ZhangLlama team, MetaPatvirtintas el. paštas meta.com
Anima AnandkumarCalifornia Institute of Technology and NVIDIAPatvirtintas el. paštas caltech.edu
Charles ElkanProfessor of Computer Science, University of California, San DiegoPatvirtintas el. paštas ucsd.edu
John BerkowitzApplePatvirtintas el. paštas apple.com
Alex SmolaBoson AIPatvirtintas el. paštas smola.org
Kamyar AzizzadenesheliNvidiaPatvirtintas el. paštas nvidia.com
Saurabh GargMistral AI | Past: CMU ML PhDPatvirtintas el. paštas andrew.cmu.edu
Julian McAuleyProfessor, UC San DiegoPatvirtintas el. paštas eng.ucsd.edu
Divyansh KaushikVice President, Beacon Global StrategiesPatvirtintas el. paštas bgsdc.com
Dave KaleData Science Manager, LiteratiPatvirtintas el. paštas literati.com
Sivaraman BalakrishnanCarnegie Mellon UniversityPatvirtintas el. paštas stat.cmu.edu
Mu LiAmazonPatvirtintas el. paštas amazon.com
Bhuwan DhingraAssistant Professor, Computer Science, Duke UniversityPatvirtintas el. paštas cs.duke.edu
Jianfeng GaoMicrosoft Research, RedmondPatvirtintas el. paštas microsoft.com
Lihong Li (李力鸿)AmazonPatvirtintas el. paštas amazon.com
Danish PruthiIndian Institute of Science, BangalorePatvirtintas el. paštas iisc.ac.in
Zico KolterCarnegie Mellon UniversityPatvirtintas el. paštas cs.cmu.edu
Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon UPatvirtintas el. paštas cs.cmu.edu
Liu LeqiUT AustinPatvirtintas el. paštas princeton.edu
Tommaso FurlanelloLeading Science at HK3 LabPatvirtintas el. paštas usc.edu

Stebėti

Zachary C. Lipton

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

Patvirtintas el. paštas cmu.edu - Pagrindinis puslapis

Machine Learning Healthcare Technology & Society NLP Robustness & Adaptivity


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
The Mythos of Model Interpretability ZC Lipton Communications of the ACM (CACM), 2016	6444*	2016
A critical review of recurrent neural networks for sequence learning ZC Lipton, J Berkowitz, C Elkan arXiv preprint arXiv:1506.00019, 2015	3794	2015
Dive into Deep Learning AJS Aston Zhang, Zachary C. Lipton, Mu Li pre-print, 2020	1798*	2020
Learning to Diagnose with LSTM Recurrent Neural Networks ZC Lipton, DC Kale, C Elkan, R Wetzell International Conference on Learning Representations (ICLR), 2015	1541	2015
Born again neural networks T Furlanello, ZC Lipton, M Tschannen, L Itti, A Anandkumar International Conference on Machine Learning (ICML), 2018	1259	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	1017	2019
Stochastic activation pruning for robust adversarial defense GS Dhillon, K Azizzadenesheli, ZC Lipton, J Bernstein, J Kossaifi, ... International Conference on Learning Representations (ICLR), 2018	716	2018
Detecting and Correcting for Label Shift with Black Box Predictors ZC Lipton, YX Wang, A Smola International Conference on Machine Learning (ICML), 2018	648	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	639	2020
What is the Effect of Importance Weighting in Deep Learning? J Byrd, Z Lipton International Conference on Machine Learning (ICML), 872-881, 2019	591	2019
Deep Active Learning for Named Entity Recognition Y Shen, H Yun, ZC Lipton, Y Kronrod, A Anandkumar International Conference on Learning Representations (ICLR), 2018	590	2018
Modeling Missing Data in Clinical Time Series with RNNs ZC Lipton, DC Kale, R Wetzel Machine Learning for Healthcare (MLHC), 2016	588*	2016
Optimal thresholding of classifiers to maximize F1 measure ZC Lipton, C Elkan, B Naryanaswamy European Conference on Machine Learning (ECML), 225-239, 2014	559	2014
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	430	2018
Differential privacy and machine learning: a survey and review Z Ji, ZC Lipton, C Elkan arXiv preprint arXiv:1412.7584, 2014	407	2014
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	359	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	342	2016
Does mitigating ML’s impact disparity require treatment disparity? ZC Lipton, A Chouldechova, J McAuley Advances in Neural Information Processing Systems (NeurIPS), 2018	282	2018
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

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