Shashanka Ubaru

According to our database, Shashanka Ubaru authored at least 38 papers between 2015 and 2024.

Collaborative distances:

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

2024

Multi-Function Multi-Way Analog Technology for Sustainable Machine Intelligence Computation.

Vassilis Kalantzis, Mark S. Squillante, Shashanka Ubaru, Tayfun Gokmen, Chai Wah Wu, Anshul Gupta, Haim Avron, Tomasz Nowicki, Malte J. Rasch, O. Murat Onen, Vanessa López-Marrero, Effendi Leobandung, Yasuteru Kohda, Wilfried Haensch, Lior Horesh

CoRR, 2024

2023

Capacity Analysis of Vector Symbolic Architectures.

Kenneth L. Clarkson, Shashanka Ubaru, Elizabeth Yang

CoRR, 2023

Quantum Graph Transformers.

Georgios Kollias, Vassilis Kalantzis, Theodoros Salonidis, Shashanka Ubaru

Proceedings of the IEEE International Conference on Acoustics, 2023

Accelerating Matrix Trace Estimation by Aitken's Δ² Process.

Vassilis Kalantzis, Georgios Kollias, Shashanka Ubaru, Theodoros Salonidis

Proceedings of the IEEE International Conference on Acoustics, 2023

Solving Sparse Linear Systems via Flexible GMRES with In-Memory Analog Preconditioning.

Vasileios Kalantzis, Mark S. Squillante, Chai Wah Wu, Anshul Gupta, Shashanka Ubaru, Tayfun Gokmen, Lior Horesh

Proceedings of the IEEE High Performance Extreme Computing Conference, 2023

2022

On Quantum Algorithms for Random Walks in the Nonnegative Quarter Plane.

Vasileios Kalantzis, Mark S. Squillante, Shashanka Ubaru, Lior Horesh

SIGMETRICS Perform. Evaluation Rev., August, 2022

Towards Quantum Advantage on Noisy Quantum Computers.

Ismail Yunus Akhalwaya, Shashanka Ubaru, Kenneth L. Clarkson, Mark S. Squillante, Vishnu Jejjala, Yang-Hui He, Kugendran Naidoo, Vasileios Kalantzis, Lior Horesh

CoRR, 2022

Randomized matrix-free quadrature for spectrum and spectral sum approximation.

Tyler Chen, Thomas Trogdon, Shashanka Ubaru

CoRR, 2022

PCENet: High Dimensional Surrogate Modeling for Learning Uncertainty.

Paz Fink Shustin, Shashanka Ubaru, Vasileios Kalantzis, Lior Horesh, Haim Avron

CoRR, 2022

Efficient Quantum Computation of the Fermionic Boundary Operator.

Ismail Yunus Akhalwaya, Yang-Hui He, Lior Horesh, Vishnu Jejjala, William Kirby, Kugendran Naidoo, Shashanka Ubaru

CoRR, 2022

2021

Dynamic graph and polynomial chaos based models for contact tracing data analysis and optimal testing prescription.

Shashanka Ubaru, Lior Horesh, Guy Cohen

J. Biomed. Informatics, 2021

Quantum Topological Data Analysis with Linear Depth and Exponential Speedup.

Shashanka Ubaru, Ismail Yunus Akhalwaya, Mark S. Squillante, Kenneth L. Clarkson, Lior Horesh

CoRR, 2021

Dynamic Graph Convolutional Networks Using the Tensor M-Product.

Osman Asif Malik, Shashanka Ubaru, Lior Horesh, Misha E. Kilmer, Haim Avron

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Efficient scaling of dynamic graph neural networks.

Venkatesan T. Chakaravarthy, Shivmaran S. Pandian, Saurabh Raje, Yogish Sabharwal, Toyotaro Suzumura, Shashanka Ubaru

Proceedings of the International Conference for High Performance Computing, 2021

Projection techniques to update the truncated SVD of evolving matrices with applications.

Vasileios Kalantzis, Georgios Kollias, Shashanka Ubaru, Athanasios N. Nikolakopoulos, Lior Horesh, Kenneth L. Clarkson

Proceedings of the 38th International Conference on Machine Learning, 2021

Analysis of stochastic Lanczos quadrature for spectrum approximation.

Tyler Chen, Thomas Trogdon, Shashanka Ubaru

Proceedings of the 38th International Conference on Machine Learning, 2021

Sparse Graph Based Sketching for Fast Numerical Linear Algebra.

Dong Hu, Shashanka Ubaru, Alex Gittens, Kenneth L. Clarkson, Lior Horesh, Vassilis Kalantzis

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Projection techniques to update the truncated SVD of evolving matrices.

Vassilis Kalantzis, Georgios Kollias, Shashanka Ubaru, Athanasios N. Nikolakopoulos, Lior Horesh, Kenneth L. Clarkson

CoRR, 2020

Dynamic graph based epidemiological model for COVID-19 contact tracing data analysis and optimal testing prescription.

Shashanka Ubaru, Lior Horesh, Guy Cohen

CoRR, 2020

Spectrum-Adapted Polynomial Approximation for Matrix Functions with Applications in Graph Signal Processing.

Tiffany Fan, David I. Shuman, Shashanka Ubaru, Yousef Saad

Algorithms, 2020

Multilabel Classification by Hierarchical Partitioning and Data-dependent Grouping.

Shashanka Ubaru, Sanjeeb Dash, Arya Mazumdar, Oktay Günlük

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Sampling and multilevel coarsening algorithms for fast matrix approximations.

Shashanka Ubaru, Yousef Saad

Numer. Linear Algebra Appl., 2019

Tensor Graph Convolutional Networks for Prediction on Dynamic Graphs.

Osman Asif Malik, Shashanka Ubaru, Lior Horesh, Misha E. Kilmer, Haim Avron

CoRR, 2019

Find the dimension that counts: Fast dimension estimation and Krylov PCA.

Shashanka Ubaru, Abd-Krim Seghouane, Yousef Saad

Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Spectrum-adapted Polynomial Approximation for Matrix Functions.

Li Fan, David I Shuman, Shashanka Ubaru, Yousef Saad

Proceedings of the IEEE International Conference on Acoustics, 2019

2018

Run Procrustes, Run! On the convergence of accelerated Procrustes Flow.

Anastasios Kyrillidis, Shashanka Ubaru, Georgios Kollias, Kristofer E. Bouchard

CoRR, 2018

Spectrum Approximation Beyond Fast Matrix Multiplication: Algorithms and Hardness.

Cameron Musco, Praneeth Netrapalli, Aaron Sidford, Shashanka Ubaru, David P. Woodruff

Proceedings of the 9th Innovations in Theoretical Computer Science Conference, 2018

2017

Low Rank Approximation and Decomposition of Large Matrices Using Error Correcting Codes.

Shashanka Ubaru, Arya Mazumdar, Yousef Saad

IEEE Trans. Inf. Theory, 2017

Fast Estimation of tr(f(A)) via Stochastic Lanczos Quadrature.

Shashanka Ubaru, Jie Chen, Yousef Saad

SIAM J. Matrix Anal. Appl., 2017

Fast Estimation of Approximate Matrix Ranks Using Spectral Densities.

Shashanka Ubaru, Yousef Saad, Abd-Krim Seghouane

Neural Comput., 2017

Improving the Incoherence of a Learned Dictionary via Rank Shrinkage.

Shashanka Ubaru, Abd-Krim Seghouane, Yousef Saad

Neural Comput., 2017

Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction.

Kristofer E. Bouchard, Alejandro F. Bujan, Farbod Roosta-Khorasani, Shashanka Ubaru, Prabhat, Antoine Snijders, Jian-Hua Mao, Edward F. Chang, Michael W. Mahoney, Sharmodeep Bhattacharyya

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

UoI-NMF Cluster: A Robust Nonnegative Matrix Factorization Algorithm for Improved Parts-Based Decomposition and Reconstruction of Noisy Data.

Shashanka Ubaru, Kesheng Wu, Kristofer E. Bouchard

Proceedings of the 16th IEEE International Conference on Machine Learning and Applications, 2017

Multilabel Classification with Group Testing and Codes.

Shashanka Ubaru, Arya Mazumdar

Proceedings of the 34th International Conference on Machine Learning, 2017

Applications of Trace Estimation Techniques.

Shashanka Ubaru, Yousef Saad

Proceedings of the High Performance Computing in Science and Engineering, 2017

2016

Group testing schemes from low-weight codewords of BCH codes.

Shashanka Ubaru, Arya Mazumdar, Alexander Barg

Proceedings of the IEEE International Symposium on Information Theory, 2016

Fast methods for estimating the Numerical rank of large matrices.

Shashanka Ubaru, Yousef Saad

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Low Rank Approximation using Error Correcting Coding Matrices.

Shashanka Ubaru, Arya Mazumdar, Yousef Saad

Proceedings of the 32nd International Conference on Machine Learning, 2015