David C. Kale

According to our database, David C. Kale authored at least 24 papers between 2009 and 2019.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2019

The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data.

Daisy Yi Ding, Chloé Simpson, Stephen Pfohl, Dave C. Kale, Kenneth Jung, Nigam H. Shah

Proceedings of the Biocomputing 2019: Proceedings of the Pacific Symposium, 2019

2017

Anchored Correlation Explanation: Topic Modeling with Minimal Domain Knowledge.

Ryan J. Gallagher, Kyle Reing, David C. Kale, Greg Ver Steeg

Trans. Assoc. Comput. Linguistics, 2017

Multitask Learning and Benchmarking with Clinical Time Series Data.

Hrayr Harutyunyan, Hrant Khachatrian, David C. Kale, Aram Galstyan

CoRR, 2017

Collecting and Analyzing Millions of mHealth Data Streams.

Tom Quisel, Luca Foschini, Alessio Signorini, David C. Kale

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

The Effectiveness of Transfer Learning in Electronic Health Records Data.

Sébastien Dubois, Nathanael Romano, Kenneth Jung, Nigam Shah, David C. Kale

Proceedings of the 5th International Conference on Learning Representations, 2017

Time Series Feature Learning with Applications to Health Care.

Zhengping Che, Sanjay Purushotham, David C. Kale, Wenzhe Li, Mohammad Taha Bahadori, Robinder G. Khemani, Yan Liu

Proceedings of the Mobile Health - Sensors, Analytic Methods, and Applications, 2017

2016

Toward Interpretable Topic Discovery via Anchored Correlation Explanation.

Kyle Reing, David C. Kale, Greg Ver Steeg, Aram Galstyan

CoRR, 2016

Intra-day Activity Better Predicts Chronic Conditions.

Tom Quisel, David C. Kale, Luca Foschini

CoRR, 2016

Learning to Diagnose with LSTM Recurrent Neural Networks.

Zachary Chase Lipton, David C. Kale, Charles Elkan, Randall C. Wetzel

Proceedings of the 4th International Conference on Learning Representations, 2016

Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time Series.

Zachary C. Lipton, David C. Kale, Randall C. Wetzel

Proceedings of the 1st Machine Learning in Health Care, 2016

2015

Learning and Optimization with Submodular Functions.

Bharath Sankaran, Marjan Ghazvininejad, Xinran He, David C. Kale, Liron Cohen

CoRR, 2015

Phenotyping of Clinical Time Series with LSTM Recurrent Neural Networks.

Zachary Chase Lipton, David C. Kale, Randall C. Wetzel

CoRR, 2015

Hierarchical Active Transfer Learning.

David C. Kale, Marjan Ghazvininejad, Anil Ramakrishna, Jingrui He, Yan Liu

Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Deep Computational Phenotyping.

Zhengping Che, David C. Kale, Wenzhe Li, Mohammad Taha Bahadori, Yan Liu

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Functional Subspace Clustering with Application to Time Series.

Mohammad Taha Bahadori, David C. Kale, Yingying Fan, Yan Liu

Proceedings of the 32nd International Conference on Machine Learning, 2015

Causal Phenotype Discovery via Deep Networks.

David C. Kale, Zhengping Che, Mohammad Taha Bahadori, Wenzhe Li, Yan Liu, Randall C. Wetzel

Proceedings of the AMIA 2015, 2015

2014

An Examination of Multivariate Time Series Hashing with Applications to Health Care.

David C. Kale, Dian Gong, Zhengping Che, Yan Liu, Gérard G. Medioni, Randall C. Wetzel, Patrick Ross

Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

Preface.

Finale Doshi-Velez, David C. Kale, Byron C. Wallace, Jenna Wiens

Proceedings of the Modern Artificial Intelligence for Health Analytics, 2014

2013

Accelerating Active Learning with Transfer Learning.

David C. Kale, Yan Liu

Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

Capturing Data Analytics Expertise with Visualizations in Workflows.

David C. Kale, Samuel Di, Yan Liu, Yolanda Gil

Proceedings of the 2013 AAAI Fall Symposia, Arlington, Virginia, USA, November 15-17, 2013, 2013

2012

Unsupervised pattern discovery in electronic health care data using probabilistic clustering models.

Benjamin M. Marlin, David C. Kale, Robinder G. Khemani, Randall C. Wetzel

Proceedings of the ACM International Health Informatics Symposium, 2012

Sim•TwentyFive: An Interactive Visualization System for Data-Driven Decision Support.

Brendan Stubbs, David C. Kale

Proceedings of the AMIA 2012, 2012

2011

An informatics architecture for the Virtual Pediatric Intensive Care Unit.

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

Proceedings of the 24th IEEE International Symposium on Computer-Based Medical Systems, 2011

2009

Estimating the position of illuminants in paintings under weak model assumptions: an application to the works of two Baroque masters.

David C. Kale, David G. Stork

Proceedings of the Human Vision and Electronic Imaging XIV, 2009