David C. Kale

31 papers A* 6A 1B 1Misc 2Journal 8Unranked 6
YearRankTypeTitle / Venue / Authors
2020 — ed.
Proceedings of the Machine Learning for Healthcare Conference, MLHC 2020, 7-8 August 2020, Virtual Event, Durham, NC, USA.
MLHC
Finale Doshi-Velez, Jim Fackler, Ken Jung, David C. Kale, Rajesh Ranganath, Byron C. Wallace, Jenna Wiens
2019 — ed.
Proceedings of the Machine Learning for Healthcare Conference, MLHC 2019, 9-10 August 2019, Ann Arbor, Michigan, USA.
MLHC
Finale Doshi-Velez, Jim Fackler, Ken Jung, David C. Kale, Rajesh Ranganath, Byron C. Wallace, Jenna Wiens
2018 — ed.
Proceedings of the Machine Learning for Healthcare Conference, MLHC 2018, 17-18 August 2018, Palo Alto, California
MLHC
Finale Doshi-Velez, Jim Fackler, Ken Jung, David C. Kale, Rajesh Ranganath, Byron C. Wallace, Jenna Wiens
2017 J jnl
Anchored Correlation Explanation: Topic Modeling with Minimal Domain Knowledge.
Trans. Assoc. Comput. Linguistics
Ryan J. Gallagher, Kyle Reing, David C. Kale, Greg Ver Steeg
2017 A* conf
Collecting and Analyzing Millions of mHealth Data Streams.
KDD
Tom Quisel, Luca Foschini, Alessio Signorini, David C. Kale
2017 J jnl
Multitask Learning and Benchmarking with Clinical Time Series Data.
CoRR
Hrayr Harutyunyan, Hrant Khachatrian, David C. Kale, Aram Galstyan
2017 — ed.
Proceedings of the Machine Learning for Healthcare Conference, MLHC 2017, Boston, Massachusetts, USA, 18-19 August 2017
MLHC
Finale Doshi-Velez, Jim Fackler, David C. Kale, Rajesh Ranganath, Byron C. Wallace, Jenna Wiens
2017 — conf
The Effectiveness of Transfer Learning in Electronic Health Records Data.
ICLR (Workshop)
Sébastien Dubois, Nathanael Romano, Kenneth Jung, Nigam Shah, David C. Kale
2017 — ch.
Time Series Feature Learning with Applications to Health Care.
Mobile Health - Sensors, Analytic Methods, and Applications
Zhengping Che, Sanjay Purushotham, David C. Kale, Wenzhe Li, Mohammad Taha Bahadori, Robinder G. Khemani, Yan Liu
2016 J jnl
Anchored Correlation Explanation: Topic Modeling with Minimal Domain Knowledge.
CoRR
Ryan J. Gallagher, Kyle Reing, David C. Kale, Greg Ver Steeg
2016 — conf
Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time Series.
MLHC
Zachary C. Lipton, David C. Kale, Randall C. Wetzel
2016 J jnl
Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time Series.
CoRR
Zachary Chase Lipton, David C. Kale, Randall C. Wetzel
2016 J jnl
Intra-day Activity Better Predicts Chronic Conditions.
CoRR
Tom Quisel, David C. Kale, Luca Foschini
2016 A* conf
Learning to Diagnose with LSTM Recurrent Neural Networks.
ICLR (Poster)
Zachary Chase Lipton, David C. Kale, Charles Elkan, Randall C. Wetzel
2016 — ed.
Proceedings of the 1st Machine Learning for Healthcare, MLHC 2016, Los Angeles, CA, USA, August 19-20, 2016
MLHC
Finale Doshi-Velez, Jim Fackler, David C. Kale, Byron C. Wallace, Jenna Wiens
2016 J jnl
Toward Interpretable Topic Discovery via Anchored Correlation Explanation.
CoRR
Kyle Reing, David C. Kale, Greg Ver Steeg, Aram Galstyan
2015 Misc conf
Causal Phenotype Discovery via Deep Networks.
AMIA
David C. Kale, Zhengping Che, Mohammad Taha Bahadori, Wenzhe Li, Yan Liu, Randall C. Wetzel
2015 A* conf
Deep Computational Phenotyping.
KDD
Zhengping Che, David C. Kale, Wenzhe Li, Mohammad Taha Bahadori, Yan Liu
2015 A* conf
Functional Subspace Clustering with Application to Time Series.
ICML
Mohammad Taha Bahadori, David C. Kale, Yingying Fan, Yan Liu
2015 A conf
Hierarchical Active Transfer Learning.
SDM
David C. Kale, Marjan Ghazvininejad, Anil Ramakrishna, Jingrui He, Yan Liu
2015 J jnl
Learning and Optimization with Submodular Functions.
CoRR
Bharath Sankaran, Marjan Ghazvininejad, Xinran He, David C. Kale, Liron Cohen
2015 J jnl
Phenotyping of Clinical Time Series with LSTM Recurrent Neural Networks.
CoRR
Zachary Chase Lipton, David C. Kale, Randall C. Wetzel
2014 A* conf
An Examination of Multivariate Time Series Hashing with Applications to Health Care.
ICDM
David C. Kale, Dian Gong, Zhengping Che, Yan Liu, Gérard G. Medioni, Randall C. Wetzel, Patrick Ross
2014 — ed.
Modern Artificial Intelligence for Health Analytics, Papers from the 2014 AAAI Workshop, Québec City, Québec, Canada, July 27, 2014
AAAI Workshop: Modern Artificial Intelligence for Health Analytics
Finale Doshi-Velez, David C. Kale, Byron C. Wallace, Jenna Wiens
2014 — conf
Preface.
AAAI Workshop: Modern Artificial Intelligence for Health Analytics
Finale Doshi-Velez, David C. Kale, Byron C. Wallace, Jenna Wiens
2013 A* conf
Accelerating Active Learning with Transfer Learning.
ICDM
David C. Kale, Yan Liu
2013 — conf
Capturing Data Analytics Expertise with Visualizations in Workflows.
AAAI Fall Symposia
David C. Kale, Samuel Di, Yan Liu, Yolanda Gil
2012 Misc conf
Sim•TwentyFive: An Interactive Visualization System for Data-Driven Decision Support.
AMIA
Brendan Stubbs, David C. Kale
2012 — conf
Unsupervised pattern discovery in electronic health care data using probabilistic clustering models.
IHI
Benjamin M. Marlin, David C. Kale, Robinder G. Khemani, Randall C. Wetzel
2011 B conf
An informatics architecture for the Virtual Pediatric Intensive Care Unit.
CBMS
Daniel J. Crichton, Chris A. Mattmann, Andrew F. Hart, David C. Kale, Robinder G. Khemani, Patrick Ross, Sarah Rubin, Paul Veeravatanayothin, Amy Braverman, Cameron Goodale, Randall C. Wetzel
2009 — conf
Estimating the position of illuminants in paintings under weak model assumptions: an application to the works of two Baroque masters.
Human Vision and Electronic Imaging
David C. Kale, David G. Stork