David C. Kale

Publication Activity (10 Years)

Years Active: 2009-2017
Publications (10 Years): 10

Top Topics

Topic Discovery

Transfer Learning

Multivariate Time Series

Recurrent Neural Networks

Top Venues

Publications

Ryan J. Gallagher, Kyle Reing, David C. Kale, Greg Ver Steeg
Anchored Correlation Explanation: Topic Modeling with Minimal Domain Knowledge. Trans. Assoc. Comput. Linguistics 5 (2017)
Hrayr Harutyunyan, Hrant Khachatrian, David C. Kale, Aram Galstyan
Multitask Learning and Benchmarking with Clinical Time Series Data. CoRR (2017)
Tom Quisel, Luca Foschini, Alessio Signorini, David C. Kale
Collecting and Analyzing Millions of mHealth Data Streams. KDD (2017)
Sébastien Dubois, Nathanael Romano, Kenneth Jung, Nigam Shah, David C. Kale
The Effectiveness of Transfer Learning in Electronic Health Records Data. ICLR (Workshop) (2017)
Zachary Chase Lipton, David C. Kale, Randall C. Wetzel
Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time Series. CoRR (2016)
Zachary C. Lipton, David C. Kale, Randall C. Wetzel
Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time Series. MLHC (2016)
Ryan J. Gallagher, Kyle Reing, David C. Kale, Greg Ver Steeg
Anchored Correlation Explanation: Topic Modeling with Minimal Domain Knowledge. CoRR (2016)
Tom Quisel, David C. Kale, Luca Foschini
Intra-day Activity Better Predicts Chronic Conditions. CoRR (2016)
Kyle Reing, David C. Kale, Greg Ver Steeg, Aram Galstyan
Toward Interpretable Topic Discovery via Anchored Correlation Explanation. CoRR (2016)
Zachary Chase Lipton, David C. Kale, Charles Elkan, Randall C. Wetzel
Learning to Diagnose with LSTM Recurrent Neural Networks. ICLR (Poster) (2016)
Zhengping Che, David C. Kale, Wenzhe Li, Mohammad Taha Bahadori, Yan Liu
Deep Computational Phenotyping. KDD (2015)
Bharath Sankaran, Marjan Ghazvininejad, Xinran He, David C. Kale, Liron Cohen
Learning and Optimization with Submodular Functions. CoRR (2015)
Zachary Chase Lipton, David C. Kale, Randall C. Wetzel
Phenotyping of Clinical Time Series with LSTM Recurrent Neural Networks. CoRR (2015)
Mohammad Taha Bahadori, David C. Kale, Yingying Fan, Yan Liu
Functional Subspace Clustering with Application to Time Series. ICML (2015)
David C. Kale, Marjan Ghazvininejad, Anil Ramakrishna, Jingrui He, Yan Liu
Hierarchical Active Transfer Learning. SDM (2015)
David C. Kale, Zhengping Che, Mohammad Taha Bahadori, Wenzhe Li, Yan Liu, Randall C. Wetzel
Causal Phenotype Discovery via Deep Networks. AMIA (2015)
Finale Doshi-Velez, David C. Kale, Byron C. Wallace, Jenna Wiens
Preface. AAAI Workshop: Modern Artificial Intelligence for Health Analytics (2014)
David C. Kale, Dian Gong, Zhengping Che, Yan Liu, Gérard G. Medioni, Randall C. Wetzel, Patrick Ross
An Examination of Multivariate Time Series Hashing with Applications to Health Care. ICDM (2014)
David C. Kale, Yan Liu
Accelerating Active Learning with Transfer Learning. ICDM (2013)
David C. Kale, Samuel Di, Yan Liu, Yolanda Gil
Capturing Data Analytics Expertise with Visualizations in Workflows. AAAI Fall Symposia (2013)
Benjamin M. Marlin, David C. Kale, Robinder G. Khemani, Randall C. Wetzel
Unsupervised pattern discovery in electronic health care data using probabilistic clustering models. IHI (2012)
Brendan Stubbs, David C. Kale
Sim•TwentyFive: An Interactive Visualization System for Data-Driven Decision Support. AMIA (2012)
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
An informatics architecture for the Virtual Pediatric Intensive Care Unit. CBMS (2011)
David C. Kale, David G. Stork
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 (2009)