David Kale
David Kale
Senior Machine Learning Scientist, Netflix
Verified email at netflix.com - Homepage
Cited by
Cited by
Learning to diagnose with LSTM recurrent neural networks
ZC Lipton, DC Kale, C Elkan, R Wetzel
arXiv preprint arXiv:1511.03677, 2015
Multitask learning and benchmarking with clinical time series data
H Harutyunyan, H Khachatrian, DC Kale, G Ver Steeg, A Galstyan
Scientific data 6 (1), 1-18, 2019
Deep computational phenotyping
Z Che, D Kale, W Li, MT Bahadori, Y Liu
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015
Do no harm: a roadmap for responsible machine learning for health care
J Wiens, S Saria, M Sendak, M Ghassemi, VX Liu, F Doshi-Velez, K Jung, ...
Nature medicine 25 (9), 1337-1340, 2019
Modeling missing data in clinical time series with rnns
ZC Lipton, DC Kale, R Wetzel
Machine Learning for Healthcare 56, 2016
Unsupervised pattern discovery in electronic health care data using probabilistic clustering models
BM Marlin, DC Kale, RG Khemani, RC Wetzel
Proceedings of the 2nd ACM SIGHIT international health informatics symposium …, 2012
Directly modeling missing data in sequences with rnns: Improved classification of clinical time series
ZC Lipton, D Kale, R Wetzel
Machine learning for healthcare conference, 253-270, 2016
Anchored correlation explanation: Topic modeling with minimal domain knowledge
RJ Gallagher, K Reing, D Kale, G Ver Steeg
Transactions of the Association for Computational Linguistics 5, 529-542, 2017
Phenotyping of clinical time series with LSTM recurrent neural networks
ZC Lipton, DC Kale, RC Wetzel
arXiv preprint arXiv:1510.07641, 2015
An examination of multivariate time series hashing with applications to health care
DC Kale, D Gong, Z Che, Y Liu, G Medioni, R Wetzel, P Ross
2014 IEEE international conference on data mining, 260-269, 2014
Accelerating active learning with transfer learning
D Kale, Y Liu
2013 IEEE 13th International Conference on Data Mining, 1085-1090, 2013
Functional subspace clustering with application to time series
MT Bahadori, D Kale, Y Fan, Y Liu
International conference on machine learning, 228-237, 2015
Causal phenotype discovery via deep networks
DC Kale, Z Che, MT Bahadori, W Li, Y Liu, R Wetzel
AMIA Annual Symposium Proceedings 2015, 677, 2015
The effect of neighborhood and individual characteristics on pediatric critical illness
D Epstein, M Reibel, JB Unger, M Cockburn, LA Escobedo, DC Kale, ...
Journal of community health 39 (4), 753-759, 2014
Hemilaminectomy for thoracolumbar Hansen Type I intervertebral disk disease in ambulatory dogs with or without neurologic deficits: 39 cases (2008–2010)
EA Ingram, DC Kale, RJ Balfour
Veterinary Surgery 42 (8), 924-931, 2013
Learning effective representations from clinical notes
S Dubois, N Romano, DC Kale, N Shah, K Jung
stat 1050, 15, 2017
Learning to diagnose with LSTM recurrent neural networks. arXiv 2015
ZC Lipton, DC Kale, C Elkan, R Wetzel
arXiv preprint arXiv:1511.03677, 0
Hierarchical active transfer learning
D Kale, M Ghazvininejad, A Ramakrishna, J He, Y Liu
Proceedings of the 2015 SIAM International Conference on Data Mining, 514-522, 2015
Collecting and analyzing millions of mhealth data streams
T Quisel, L Foschini, A Signorini, DC Kale
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017
Estimating the position of illuminants in paintings under weak model assumptions: An application to the works of two Baroque masters
D Kale, DG Stork
Human Vision and Electronic Imaging XIV 7240, 72401M, 2009
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