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ORCIDSrinivas Eswar
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Books and Theses
- 2022
[b1]Srinivas Eswar:
Scalable Data Mining via Constrained Low Rank Approximation. Georgia Institute of Technology, Atlanta, GA, USA, 2022
Journal Articles
- 2021
- [j5]Srinivas Eswar
, Ramakrishnan Kannan, Richard W. Vuduc, Haesun Park:
ORCA: Outlier detection and Robust Clustering for Attributed graphs. J. Glob. Optim. 81(4): 967-989 (2021) - [j4]Delin Chu, Weya Shi, Srinivas Eswar, Haesun Park:
An Alternating Rank-k Nonnegative Least Squares Framework (ARkNLS) for Nonnegative Matrix Factorization. SIAM J. Matrix Anal. Appl. 42(4): 1451-1479 (2021) - [j3]Srinivas Eswar, Koby Hayashi, Grey Ballard, Ramakrishnan Kannan, Michael A. Matheson, Haesun Park:
PLANC: Parallel Low-rank Approximation with Nonnegativity Constraints. ACM Trans. Math. Softw. 47(3): 20:1-20:37 (2021) - 2020
- [j2]Eric R. Hein, Srinivas Eswar, Abdurrahman Yasar, Jiajia Li, Jeffrey S. Young, Thomas M. Conte, Ümit V. Çatalyürek, Richard W. Vuduc, E. Jason Riedy, Bora Uçar:
Programming Strategies for Irregular Algorithms on the Emu Chick. ACM Trans. Parallel Comput. 7(4): 25:1-25:25 (2020) - 2019
- [j1]Jeffrey S. Young, Eric R. Hein, Srinivas Eswar, Patrick Lavin, Jiajia Li, E. Jason Riedy, Richard W. Vuduc, Tom Conte:
A microbenchmark characterization of the Emu chick. Parallel Comput. 87: 60-69 (2019)
Conference and Workshop Papers
- 2023
- [c4]Srinivas Eswar, Benjamin Cobb, Koby Hayashi, Ramakrishnan Kannan, Grey Ballard, Richard W. Vuduc, Haesun Park:
Distributed-Memory Parallel JointNMF. ICS 2023: 301-312 - 2020
- [c3]Srinivas Eswar, Koby Hayashi, Grey Ballard, Ramakrishnan Kannan, Richard W. Vuduc, Haesun Park:
Distributed-memory parallel symmetric nonnegative matrix factorization. SC 2020: 74 - 2019
- [c2]Piyush Sao, Christian Engelmann, Srinivas Eswar, Oded Green, Richard W. Vuduc:
Self-stabilizing Connected Components. FTXS@SC 2019: 50-59 - 2018
- [c1]Eric R. Hein, Tom Conte, Jeffrey Young, Srinivas Eswar, Jiajia Li, Patrick Lavin, Richard W. Vuduc, E. Jason Riedy:
An Initial Characterization of the Emu Chick. IPDPS Workshops 2018: 579-588
Data and Artifacts
- 2023
- [d2]Srinivas Eswar, Benjamin Cobb, Koby Hayashi, Ramakrishnan Kannan, Grey Ballard, Rich Vuduc, Haesun Park:
AminerMag S Dataset. Zenodo, 2023
- [d1]Srinivas Eswar, Benjamin Cobb, Koby Hayashi, Ramakrishnan Kannan, Grey Ballard, Rich Vuduc, Haesun Park:
AminerMag X Dataset. Zenodo, 2023
Informal and Other Publications
- 2024
- [i5]Srinivas Eswar, Vishwas Rao, Arvind K. Saibaba:
Bayesian D-Optimal Experimental Designs via Column Subset Selection: The Power of Reweighted Sensors. CoRR abs/2402.16000 (2024) - 2020
- [i4]Delin Chu, Wenya Shi, Srinivas Eswar, Haesun Park:
An Alternating Rank-K Nonnegative Least Squares Framework (ARkNLS) for Nonnegative Matrix Factorization. CoRR abs/2007.06118 (2020) - 2019
- [i3]Eric R. Hein, Srinivas Eswar, Abdurrahman Yasar, Jiajia Li, Jeffrey S. Young, Thomas M. Conte, Ümit V. Çatalyürek, Rich Vuduc, E. Jason Riedy, Bora Uçar:
Programming Strategies for Irregular Algorithms on the Emu Chick. CoRR abs/1901.02775 (2019) - [i2]Srinivas Eswar, Koby Hayashi, Grey Ballard, Ramakrishnan Kannan, Michael A. Matheson, Haesun Park:
PLANC: Parallel Low Rank Approximation with Non-negativity Constraints. CoRR abs/1909.01149 (2019) - 2018
- [i1]Jeffrey Young, Eric R. Hein, Srinivas Eswar, Patrick Lavin, Jiajia Li, E. Jason Riedy, Richard W. Vuduc, Tom Conte:
A Microbenchmark Characterization of the Emu Chick. CoRR abs/1809.07696 (2018)
Coauthor Index
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