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Randomized Algorithms for Scientific Computing (RASC)


Apr 19, 2021
Aydin Buluc, Tamara G. Kolda, Stefan M. Wild, Mihai Anitescu, Anthony DeGennaro, John Jakeman, Chandrika Kamath, Ramakrishnan, Kannan, Miles E. Lopes, Per-Gunnar Martinsson, Kary Myers, Jelani Nelson, Juan M. Restrepo, C. Seshadhri, Draguna Vrabie, Brendt Wohlberg, Stephen J. Wright, Chao Yang, Peter Zwart


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PersGNN: Applying Topological Data Analysis and Geometric Deep Learning to Structure-Based Protein Function Prediction


Oct 30, 2020
Nicolas Swenson, Aditi S. Krishnapriyan, Aydin Buluc, Dmitriy Morozov, Katherine Yelick

* The first two authors contributed equally to this work 

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Reducing Communication in Graph Neural Network Training


May 07, 2020
Alok Tripathy, Katherine Yelick, Aydin Buluc


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Integrated Model, Batch and Domain Parallelism in Training Neural Networks


May 16, 2018
Amir Gholami, Ariful Azad, Peter Jin, Kurt Keutzer, Aydin Buluc

* 30th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2018 
* 11 pages 

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Communication-Avoiding Optimization Methods for Distributed Massive-Scale Sparse Inverse Covariance Estimation


Apr 08, 2018
Penporn Koanantakool, Alnur Ali, Ariful Azad, Aydin Buluc, Dmitriy Morozov, Leonid Oliker, Katherine Yelick, Sang-Yun Oh

* Main paper: 15 pages, appendix: 24 pages 

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