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ORCIDAditya Devarakonda
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2020 – today
- 2024
[c6]Aditya Devarakonda, Grey Ballard:
Sequential and Shared-Memory Parallel Algorithms for Partitioned Local Depths. PP 2024: 53-64- [i8]Zishan Shao, Aditya Devarakonda:
Scalable Dual Coordinate Descent for Kernel Methods. CoRR abs/2406.18001 (2024) - 2023
- [i7]Aditya Devarakonda, Grey Ballard:
Sequential and Shared-Memory Parallel Algorithms for Partitioned Local Depths. CoRR abs/2307.16652 (2023) - 2020
- [c5]Aditya Devarakonda
, James Demmel:
Avoiding Communication in Logistic Regression. HiPC 2020: 91-100 - [i6]Aditya Devarakonda, James Demmel:
Avoiding Communication in Logistic Regression. CoRR abs/2011.08281 (2020)
2010 – 2019
- 2019
- [j3]Aditya Devarakonda, Kimon Fountoulakis, James Demmel, Michael W. Mahoney:
Avoiding Communication in Primal and Dual Block Coordinate Descent Methods. SIAM J. Sci. Comput. 41(1): C1-C27 (2019) - 2018
- [b1]Aditya Devarakonda:
Avoiding Communication in First Order Methods for Optimization. University of California, Berkeley, USA, 2018 - [c4]Saeed Soori, Aditya Devarakonda, Zachary Blanco, James Demmel, Mert Gürbüzbalaban, Maryam Mehri Dehnavi:
Reducing Communication in Proximal Newton Methods for Sparse Least Squares Problems. ICPP 2018: 22:1-22:10 - [c3]Aditya Devarakonda, Kimon Fountoulakis, James Demmel, Michael W. Mahoney:
Avoiding Synchronization in First-Order Methods for Sparse Convex Optimization. IPDPS 2018: 409-418 - 2017
- [i5]Saeed Soori, Aditya Devarakonda, James Demmel, Mert Gürbüzbalaban, Maryam Mehri Dehnavi:
Avoiding Communication in Proximal Methods for Convex Optimization Problems. CoRR abs/1710.08883 (2017) - [i4]Aditya Devarakonda, Maxim Naumov, Michael Garland:
AdaBatch: Adaptive Batch Sizes for Training Deep Neural Networks. CoRR abs/1712.02029 (2017) - [i3]Aditya Devarakonda, Kimon Fountoulakis, James Demmel, Michael W. Mahoney:
Avoiding Synchronization in First-Order Methods for Sparse Convex Optimization. CoRR abs/1712.06047 (2017) - 2016
- [c2]Alex Gittens, Aditya Devarakonda, Evan Racah, Michael F. Ringenburg, Lisa Gerhardt, Jey Kottalam, Jialin Liu, Kristyn J. Maschhoff, Shane Canon, Jatin Chhugani, Pramod Sharma, Jiyan Yang, James Demmel, Jim Harrell, Venkat Krishnamurthy, Michael W. Mahoney, Prabhat:
Matrix factorizations at scale: A comparison of scientific data analytics in spark and C+MPI using three case studies. IEEE BigData 2016: 204-213 - [i2]Alex Gittens, Aditya Devarakonda, Evan Racah, Michael F. Ringenburg, Lisa Gerhardt, Jey Kottalam, Jialin Liu, Kristyn J. Maschhoff, Shane Canon, Jatin Chhugani, Pramod Sharma, Jiyan Yang, James Demmel, Jim Harrell, Venkat Krishnamurthy, Michael W. Mahoney, Prabhat:
Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies. CoRR abs/1607.01335 (2016) - [i1]Aditya Devarakonda, Kimon Fountoulakis, James Demmel, Michael W. Mahoney:
Avoiding communication in primal and dual block coordinate descent methods. CoRR abs/1612.04003 (2016) - 2014
- [c1]Razvan Carbunescu, Aditya Devarakonda, James Demmel, Steven I. Gordon, Jay Alameda, Susan Mehringer:
Architecting an autograder for parallel code. XSEDE 2014: 68:1-68:8 - 2013
- [j2]Manish Parashar, Moustafa AbdelBaky, Ivan Rodero, Aditya Devarakonda:
Cloud Paradigms and Practices for Computational and Data-Enabled Science and Engineering. Comput. Sci. Eng. 15(4): 10-18 (2013) - 2012
- [j1]David Villegas, Norman Bobroff, Ivan Rodero, Javier Delgado, Yanbin Liu, Aditya Devarakonda, Liana Fong, Seyed Masoud Sadjadi, Manish Parashar:
Cloud federation in a layered service model. J. Comput. Syst. Sci. 78(5): 1330-1344 (2012)
Coauthor Index
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