Low Rank Approximation using Error Correcting Coding Matrices. - Shashanka Ubaru; Arya Mazumdar; Yousef Saad (ICML, 2015)

Fast methods for estimating the Numerical rank of large matrices. - Shashanka Ubaru; Yousef Saad (ICML, 2016)

Group testing schemes from low-weight codewords of BCH codes. - Shashanka Ubaru; Arya Mazumdar; Alexander Barg (ISIT, 2016)

Applications of Trace Estimation Techniques. - Shashanka Ubaru; Yousef Saad (HPCSE, 2017)

Multilabel Classification with Group Testing and Codes. - Shashanka Ubaru; Arya Mazumdar (ICML, 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 (ICMLA, 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 (NIPS, 2017)

Improving the Incoherence of a Learned Dictionary via Rank Shrinkage. - Shashanka Ubaru; Abd-Krim Seghouane; Yousef Saad (Neural Comput., 2017)

Fast Estimation of Approximate Matrix Ranks Using Spectral Densities. - Shashanka Ubaru; Yousef Saad; Abd-Krim Seghouane (Neural Comput., 2017)

Fast Estimation of tr(f(A)) via Stochastic Lanczos Quadrature. - Shashanka Ubaru; Jie Chen 007; Yousef Saad (SIAM J. Matrix Anal. Appl., 2017)

Low Rank Approximation and Decomposition of Large Matrices Using Error Correcting Codes. - Shashanka Ubaru; Arya Mazumdar; Yousef Saad (IEEE Trans. Inf. Theory, 2017)

Spectrum Approximation Beyond Fast Matrix Multiplication: Algorithms and Hardness. - Cameron Musco; Praneeth Netrapalli; Aaron Sidford; Shashanka Ubaru; David P. Woodruff (ITCS, 2018)

Run Procrustes, Run! On the convergence of accelerated Procrustes Flow. - Anastasios Kyrillidis; Shashanka Ubaru; Georgios Kollias; Kristofer E. Bouchard (CoRR, 2018)

Spectrum-adapted Polynomial Approximation for Matrix Functions. - Li Fan; David I Shuman; Shashanka Ubaru; Yousef Saad (ICASSP, 2019)

Find the dimension that counts: Fast dimension estimation and Krylov PCA. - Shashanka Ubaru; Abd-Krim Seghouane; Yousef Saad (SDM, 2019)

Tensor Graph Convolutional Networks for Prediction on Dynamic Graphs. - Osman Asif Malik; Shashanka Ubaru; Lior Horesh; Misha E. Kilmer; Haim Avron (CoRR, 2019)

Sampling and multilevel coarsening algorithms for fast matrix approximations. - Shashanka Ubaru; Yousef Saad (Numer. Linear Algebra Appl., 2019)

Multilabel Classification by Hierarchical Partitioning and Data-dependent Grouping. - Shashanka Ubaru; Sanjeeb Dash; Arya Mazumdar; Oktay Günlük (NeurIPS, 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)

Dynamic graph based epidemiological model for COVID-19 contact tracing data analysis and optimal testing prescription. - Shashanka Ubaru; Lior Horesh; Guy Cohen (CoRR, 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)

Sparse Graph Based Sketching for Fast Numerical Linear Algebra. - Dong Hu; Shashanka Ubaru; Alex Gittens; Kenneth L. Clarkson; Lior Horesh; Vassilis Kalantzis (ICASSP, 2021)

Analysis of stochastic Lanczos quadrature for spectrum approximation. - Tyler Chen; Thomas Trogdon; Shashanka Ubaru (ICML, 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 (ICML, 2021)

Efficient scaling of dynamic graph neural networks. - Venkatesan T. Chakaravarthy; Shivmaran S. Pandian; Saurabh Raje; Yogish Sabharwal; Toyotaro Suzumura; Shashanka Ubaru (SC, 2021)

Dynamic Graph Convolutional Networks Using the Tensor M-Product. - Osman Asif Malik; Shashanka Ubaru; Lior Horesh; Misha E. Kilmer; Haim Avron (SDM, 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 and polynomial chaos based models for contact tracing data analysis and optimal testing prescription. - Shashanka Ubaru; Lior Horesh; Guy Cohen (J. Biomed. Informatics, 2021)

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)

PCENet: High Dimensional Surrogate Modeling for Learning Uncertainty. - Paz Fink Shustin; Shashanka Ubaru; Vasileios Kalantzis; Lior Horesh; Haim Avron (CoRR, 2022)

Randomized matrix-free quadrature for spectrum and spectral sum approximation. - Tyler Chen; Thomas Trogdon; Shashanka Ubaru (CoRR, 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)

On Quantum Algorithms for Random Walks in the Nonnegative Quarter Plane. - Vasileios Kalantzis; Mark S. Squillante; Shashanka Ubaru; Lior Horesh (SIGMETRICS Perform. Evaluation Rev., 2022)

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 (HPEC, 2023)

Accelerating Matrix Trace Estimation by Aitken's Δ2 Process. - Vassilis Kalantzis; Georgios Kollias; Shashanka Ubaru; Theodoros Salonidis (ICASSP, 2023)

Quantum Graph Transformers. - Georgios Kollias; Vassilis Kalantzis; Theodoros Salonidis; Shashanka Ubaru (ICASSP, 2023)

Capacity Analysis of Vector Symbolic Architectures. - Kenneth L. Clarkson; Shashanka Ubaru; Elizabeth Yang (CoRR, 2023)

Asynchronous Randomized Trace Estimation. - Vasileios Kalantzis; Shashanka Ubaru; Chai Wah Wu; Georgios Kollias; Lior Horesh (AISTATS, 2024)

Topological data analysis 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 (ICLR, 2024)

Counting Triangles of Graphs via Matrix Partitioning. - Georgios Kollias; Vassilis Kalantzis; Lior Horesh; Shashanka Ubaru; Panagiotis A. Traganitis (MLSP, 2024)

Single-pass top-N subgraph centrality of graphs via subspace projections. - Vassilis Kalantzis; Georgios Kollias; Shashanka Ubaru; Naoki Abe; Lior Horesh (J. Complex Networks, 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; et al. (CoRR, 2024)

On Quantum Algorithms for Efficient Solutions of General Classes of Structured Markov Processes. - Vasileios Kalantzis; Mark S. Squillante; Shashanka Ubaru (SIGMETRICS Perform. Evaluation Rev., 2024)

Multivariate Trace Estimation Using Quantum State Space Linear Algebra. - Liron Mor-Yosef; Shashanka Ubaru; Lior Horesh; Haim Avron (SIAM J. Matrix Anal. Appl., 2025)

Randomized Matrix-Free Quadrature: Unified and Uniform Bounds for Stochastic Lanczos Quadrature and the Kernel Polynomial Method. - Tyler Chen; Thomas Trogdon; Shashanka Ubaru (SIAM J. Sci. Comput., 2025)

Combinatorial Multi-armed Bandits: Arm Selection via Group Testing. - Arpan Mukherjee; Shashanka Ubaru; Keerthiram Murugesan; Karthikeyan Shanmugam; Ali Tajer (Trans. Mach. Learn. Res., 2025)

Transformers Learn Faster with Semantic Focus. - Parikshit Ram; Kenneth L. Clarkson; Tim Klinger; Shashanka Ubaru; Alexander G. Gray (CoRR, 2025)