34 citations · 58 across the 6 of their papers we have counts for
9 papers
Multivariate trace estimation using quantum state space linear algebra
Liron Mor Yosef, Shashanka Ubaru, Lior Horesh +1
In this paper, we present a quantum algorithm for approximating multivariate traces, i.e. the traces of matrix products. Our research is motivated by the extensive utility of multi…
Efficient Scaling of Dynamic Graph Neural Networks
Venkatesan T. Chakaravarthy, Shivmaran S. Pandian, Saurabh Raje +3
We present distributed algorithms for training dynamic Graph Neural Networks (GNN) on large scale graphs spanning multi-node, multi-GPU systems. To the best of our knowledge, this…
Quantum Topological Data Analysis with Linear Depth and Exponential Speedup
Shashanka Ubaru, Ismail Yunus Akhalwaya, Mark S. Squillante +2
Quantum computing offers the potential of exponential speedups for certain classical computations. Over the last decade, many quantum machine learning (QML) algorithms have been pr…
Analysis of stochastic Lanczos quadrature for spectrum approximation
Tyler Chen, Thomas Trogdon, Shashanka Ubaru
The cumulative empirical spectral measure (CESM) of a symmetric matrix is defined as the fraction of eigenvalues of…
Sparse graph based sketching for fast numerical linear algebra
Dong Hu, Shashanka Ubaru, Alex Gittens +3
In recent years, a variety of randomized constructions of sketching matrices have been devised, that have been used in fast algorithms for numerical linear algebra problems, such a…
Projection techniques to update the truncated SVD of evolving matrices
Vassilis Kalantzis, Georgios Kollias, Shashanka Ubaru +3
This paper considers the problem of updating the rank-k truncated Singular Value Decomposition (SVD) of matrices subject to the addition of new rows and/or columns over time. Such…