Srinivas Eswar

According to our database, Srinivas Eswar authored at least 18 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Structured Column Subset Selection for Bayesian Optimal Experimental Design.

Hugo Díaz, Arvind K. Saibaba, Srinivas Eswar, Vishwas Rao, Zichao Wendy Di

CoRR, June, 2025

Brief Announcement: Optimality Conditions for Parallel Communication-Avoiding Matrix Multiplication with Overlapped Communication.

Mikhail Isaev, Srinivas Eswar, Richard W. Vuduc

Proceedings of the 37th ACM Symposium on Parallelism in Algorithms and Architectures, 2025

2024

Bayesian D-Optimal Experimental Designs via Column Subset Selection: The Power of Reweighted Sensors.

Srinivas Eswar, Vishwas Rao, Arvind K. Saibaba

CoRR, 2024

On Rank Selection for Nonnegative Matrix Factorization.

Srinivas Eswar, Koby Hayashi, Benjamin Cobb, Ramakrishnan Kannan, Grey Ballard, Richard W. Vuduc, Haesun Park

Proceedings of the IEEE International Conference on Big Data, 2024

2023

AminerMag X Dataset.

Srinivas Eswar, Benjamin Cobb, Koby Hayashi, Ramakrishnan Kannan, Grey Ballard, Rich Vuduc, Haesun Park

Dataset, June, 2023

AminerMag S Dataset.

Srinivas Eswar, Benjamin Cobb, Koby Hayashi, Ramakrishnan Kannan, Grey Ballard, Rich Vuduc, Haesun Park

Dataset, June, 2023

Distributed-Memory Parallel JointNMF.

Srinivas Eswar, Benjamin Cobb, Koby Hayashi, Ramakrishnan Kannan, Grey Ballard, Richard W. Vuduc, Haesun Park

Proceedings of the 37th International Conference on Supercomputing, 2023

2022

Scalable Data Mining via Constrained Low Rank Approximation.

Srinivas Eswar

PhD thesis, 2022

2021

PLANC: Parallel Low-rank Approximation with Nonnegativity Constraints.

Srinivas Eswar, Koby Hayashi, Grey Ballard, Ramakrishnan Kannan, Michael A. Matheson, Haesun Park

ACM Trans. Math. Softw., 2021

An Alternating Rank-<i>k</i> Nonnegative Least Squares Framework (ARkNLS) for Nonnegative Matrix Factorization.

Delin Chu, Weya Shi, Srinivas Eswar, Haesun Park

SIAM J. Matrix Anal. Appl., 2021

ORCA: Outlier detection and Robust Clustering for Attributed graphs.

Srinivas Eswar, Ramakrishnan Kannan, Richard W. Vuduc, Haesun Park

J. Glob. Optim., 2021

2020

Programming Strategies for Irregular Algorithms on the Emu Chick.

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

ACM Trans. Parallel Comput., 2020

An Alternating Rank-K Nonnegative Least Squares Framework (ARkNLS) for Nonnegative Matrix Factorization.

Delin Chu, Wenya Shi, Srinivas Eswar, Haesun Park

CoRR, 2020

Distributed-memory parallel symmetric nonnegative matrix factorization.

Srinivas Eswar, Koby Hayashi, Grey Ballard, Ramakrishnan Kannan, Richard W. Vuduc, Haesun Park

Proceedings of the International Conference for High Performance Computing, 2020

2019

A microbenchmark characterization of the Emu chick.

Jeffrey S. Young, Eric R. Hein, Srinivas Eswar, Patrick Lavin, Jiajia Li, E. Jason Riedy, Richard W. Vuduc, Tom Conte

Parallel Comput., 2019

PLANC: Parallel Low Rank Approximation with Non-negativity Constraints.

Srinivas Eswar, Koby Hayashi, Grey Ballard, Ramakrishnan Kannan, Michael A. Matheson, Haesun Park

CoRR, 2019

Self-stabilizing Connected Components.

Piyush Sao, Christian Engelmann, Srinivas Eswar, Oded Green, Richard W. Vuduc

Proceedings of the 9th IEEE/ACM Workshop on Fault Tolerance for HPC at eXtreme Scale, 2019

2018

An Initial Characterization of the Emu Chick.

Eric R. Hein, Tom Conte, Jeffrey Young, Srinivas Eswar, Jiajia Li, Patrick Lavin, Richard W. Vuduc, E. Jason Riedy

Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium Workshops, 2018