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Large Scale Neural Architecture Search with Polyharmonic Splines


Nov 20, 2020
Ulrich Finkler, Michele Merler, Rameswar Panda, Mayoore S. Jaiswal, Hui Wu, Kandan Ramakrishnan, Chun-Fu Chen, Minsik Cho, David Kung, Rogerio Feris, Bishwaranjan Bhattacharjee


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NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search


Jun 23, 2020
Rameswar Panda, Michele Merler, Mayoore Jaiswal, Hui Wu, Kandan Ramakrishnan, Ulrich Finkler, Chun-Fu Chen, Minsik Cho, David Kung, Rogerio Feris, Bishwaranjan Bhattacharjee

* 19 pages, 19 Figures, 6 Tables 

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SimEx: Express Prediction of Inter-dataset Similarity by a Fleet of Autoencoders


Jan 14, 2020
Inseok Hwang, Jinho Lee, Frank Liu, Minsik Cho

* 12 pages 

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Enabling real-time multi-messenger astrophysics discoveries with deep learning


Nov 26, 2019
E. A. Huerta, Gabrielle Allen, Igor Andreoni, Javier M. Antelis, Etienne Bachelet, Bruce Berriman, Federica Bianco, Rahul Biswas, Matias Carrasco, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Maya Fishbach, Francisco Förster, Daniel George, Tom Gibbs, Matthew Graham, William Gropp, Robert Gruendl, Anushri Gupta, Roland Haas, Sarah Habib, Elise Jennings, Margaret W. G. Johnson, Erik Katsavounidis, Daniel S. Katz, Asad Khan, Volodymyr Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Zsuzsa Marka, Kenton McHenry, Jonah Miller, Claudia Moreno, Mark Neubauer, Steve Oberlin, Alexander R. Olivas, Donald Petravick, Adam Rebei, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard F. Schutz, Alex Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Leo Singer, Brigitta M. Sipőcz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, Jinjun Xiong, Zhizhen Zhao

* Nature Reviews Physics volume 1, pages 600-608 (2019) 
* Invited Expert Recommendation for Nature Reviews Physics. The art work produced by E. A. Huerta and Shawn Rosofsky for this article was used by Carl Conway to design the cover of the October 2019 issue of Nature Reviews Physics 

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MUTE: Data-Similarity Driven Multi-hot Target Encoding for Neural Network Design


Oct 15, 2019
Mayoore S. Jaiswal, Bumboo Kang, Jinho Lee, Minsik Cho

* NeurIPS Workshop 2019 - Learning with Rich Experience: Integration of Learning Paradigms 

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Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era


Feb 01, 2019
Gabrielle Allen, Igor Andreoni, Etienne Bachelet, G. Bruce Berriman, Federica B. Bianco, Rahul Biswas, Matias Carrasco Kind, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Daniel George, Tom Gibbs, Matthew Graham, William Gropp, Anushri Gupta, Roland Haas, E. A. Huerta, Elise Jennings, Daniel S. Katz, Asad Khan, Volodymyr Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Kenton McHenry, J. M. Miller, M. S. Neubauer, Steve Oberlin, Alexander R. Olivas Jr, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard Schutz, Alex Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Brigitta M. Sipőcz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, Jinjun Xiong, Zhizhen Zhao

* 15 pages, no figures. White paper based on the "Deep Learning for Multi-Messenger Astrophysics: Real-time Discovery at Scale" workshop, hosted at NCSA, October 17-19, 2018 http://www.ncsa.illinois.edu/Conferences/DeepLearningLSST/ 

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Data-parallel distributed training of very large models beyond GPU capacity


Nov 29, 2018
Samuel Matzek, Max Grossman, Minsik Cho, Anar Yusifov, Bryant Nelson, Amit Juneja


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A Unified Approximation Framework for Deep Neural Networks


Jul 27, 2018
Yuzhe Ma, Ran Chen, Wei Li, Fanhua Shang, Wenjian Yu, Minsik Cho, Bei Yu

* 10 pages, 4 figures, 2 tables 

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PowerAI DDL


Aug 07, 2017
Minsik Cho, Ulrich Finkler, Sameer Kumar, David Kung, Vaibhav Saxena, Dheeraj Sreedhar


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MEC: Memory-efficient Convolution for Deep Neural Network


Jun 21, 2017
Minsik Cho, Daniel Brand

* ICML2017 

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