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Shashanka Ubaru
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2020 – today
- 2024
- [c22]Vasileios Kalantzis, Shashanka Ubaru, Chai Wah Wu, Georgios Kollias, Lior Horesh:
Asynchronous Randomized Trace Estimation. AISTATS 2024: 4294-4302 - [c21]Ismail Yunus Akhalwaya, Shashanka Ubaru, Kenneth L. Clarkson, Mark S. Squillante, Vishnu Jejjala, Yang-Hui He, Kugendran Naidoo, Vasileios Kalantzis, Lior Horesh:
Topological data analysis on noisy quantum computers. ICLR 2024 - [c20]Georgios Kollias, Vassilis Kalantzis, Lior Horesh, Shashanka Ubaru, Panagiotis A. Traganitis:
Counting Triangles of Graphs via Matrix Partitioning. MLSP 2024: 1-6 - [i24]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:
Multi-Function Multi-Way Analog Technology for Sustainable Machine Intelligence Computation. CoRR abs/2401.13754 (2024) - [i23]Vasileios Kalantzis, Mark S. Squillante, Shashanka Ubaru:
On Quantum Algorithms for Efficient Solutions of General Classes of Structured Markov Processes. CoRR abs/2404.17959 (2024) - [i22]Liron Mor-Yosef, Shashanka Ubaru, Lior Horesh, Haim Avron:
Multivariate trace estimation using quantum state space linear algebra. CoRR abs/2405.01098 (2024) - [i21]Arpan Mukherjee, Shashanka Ubaru, Keerthiram Murugesan, Karthikeyan Shanmugam, Ali Tajer:
Combinatorial Multi-armed Bandits: Arm Selection via Group Testing. CoRR abs/2410.10679 (2024) - 2023
- [c19]Vasileios Kalantzis, Mark S. Squillante, Chai Wah Wu, Anshul Gupta, Shashanka Ubaru, Tayfun Gokmen, Lior Horesh:
Solving Sparse Linear Systems via Flexible GMRES with In-Memory Analog Preconditioning. HPEC 2023: 1-7 - [c18]Vassilis Kalantzis, Georgios Kollias, Shashanka Ubaru, Theodoros Salonidis:
Accelerating Matrix Trace Estimation by Aitken's Δ2 Process. ICASSP 2023: 1-5 - [c17]Georgios Kollias, Vassilis Kalantzis, Theodoros Salonidis, Shashanka Ubaru:
Quantum Graph Transformers. ICASSP 2023: 1-5 - [i20]Kenneth L. Clarkson, Shashanka Ubaru, Elizabeth Yang:
Capacity Analysis of Vector Symbolic Architectures. CoRR abs/2301.10352 (2023) - 2022
- [j8]Vasileios Kalantzis, Mark S. Squillante, Shashanka Ubaru, Lior Horesh:
On Quantum Algorithms for Random Walks in the Nonnegative Quarter Plane. SIGMETRICS Perform. Evaluation Rev. 50(2): 42-44 (2022) - [i19]Ismail Yunus Akhalwaya, Yang-Hui He, Lior Horesh, Vishnu Jejjala, William Kirby, Kugendran Naidoo, Shashanka Ubaru:
Efficient Quantum Computation of the Fermionic Boundary Operator. CoRR abs/2201.11510 (2022) - [i18]Paz Fink Shustin, Shashanka Ubaru, Vasileios Kalantzis, Lior Horesh, Haim Avron:
PCENet: High Dimensional Surrogate Modeling for Learning Uncertainty. CoRR abs/2202.05063 (2022) - [i17]Tyler Chen, Thomas Trogdon, Shashanka Ubaru:
Randomized matrix-free quadrature for spectrum and spectral sum approximation. CoRR abs/2204.01941 (2022) - [i16]Ismail Yunus Akhalwaya, Shashanka Ubaru, Kenneth L. Clarkson, Mark S. Squillante, Vishnu Jejjala, Yang-Hui He, Kugendran Naidoo, Vasileios Kalantzis, Lior Horesh:
Towards Quantum Advantage on Noisy Quantum Computers. CoRR abs/2209.09371 (2022) - 2021
- [j7]Shashanka Ubaru, Lior Horesh, Guy Cohen:
Dynamic graph and polynomial chaos based models for contact tracing data analysis and optimal testing prescription. J. Biomed. Informatics 122: 103901 (2021) - [c16]Dong Hu, Shashanka Ubaru, Alex Gittens, Kenneth L. Clarkson, Lior Horesh, Vassilis Kalantzis:
Sparse Graph Based Sketching for Fast Numerical Linear Algebra. ICASSP 2021: 3255-3259 - [c15]Tyler Chen, Thomas Trogdon, Shashanka Ubaru:
Analysis of stochastic Lanczos quadrature for spectrum approximation. ICML 2021: 1728-1739 - [c14]Vasileios Kalantzis, Georgios Kollias, Shashanka Ubaru, Athanasios N. Nikolakopoulos, Lior Horesh, Kenneth L. Clarkson:
Projection techniques to update the truncated SVD of evolving matrices with applications. ICML 2021: 5236-5246 - [c13]Venkatesan T. Chakaravarthy, Shivmaran S. Pandian, Saurabh Raje, Yogish Sabharwal, Toyotaro Suzumura, Shashanka Ubaru:
Efficient scaling of dynamic graph neural networks. SC 2021: 77 - [c12]Osman Asif Malik, Shashanka Ubaru, Lior Horesh, Misha E. Kilmer, Haim Avron:
Dynamic Graph Convolutional Networks Using the Tensor M-Product. SDM 2021: 729-737 - [i15]Dong Hu, Shashanka Ubaru, Alex Gittens, Kenneth L. Clarkson, Lior Horesh, Vassilis Kalantzis:
Sparse graph based sketching for fast numerical linear algebra. CoRR abs/2102.05758 (2021) - [i14]Tyler Chen, Thomas Trogdon, Shashanka Ubaru:
Analysis of stochastic Lanczos quadrature for spectrum approximation. CoRR abs/2105.06595 (2021) - [i13]Shashanka Ubaru, Ismail Yunus Akhalwaya, Mark S. Squillante, Kenneth L. Clarkson, Lior Horesh:
Quantum Topological Data Analysis with Linear Depth and Exponential Speedup. CoRR abs/2108.02811 (2021) - [i12]Venkatesan T. Chakaravarthy, Shivmaran S. Pandian, Saurabh Raje, Yogish Sabharwal, Toyotaro Suzumura, Shashanka Ubaru:
Efficient Scaling of Dynamic Graph Neural Networks. CoRR abs/2109.07893 (2021) - 2020
- [j6]Tiffany Fan, David I. Shuman, Shashanka Ubaru, Yousef Saad:
Spectrum-Adapted Polynomial Approximation for Matrix Functions with Applications in Graph Signal Processing. Algorithms 13(11): 295 (2020) - [c11]Shashanka Ubaru, Sanjeeb Dash, Arya Mazumdar, Oktay Günlük:
Multilabel Classification by Hierarchical Partitioning and Data-dependent Grouping. NeurIPS 2020 - [i11]Shashanka Ubaru, Sanjeeb Dash, Arya Mazumdar, Oktay Günlük:
Multilabel Classification by Hierarchical Partitioning and Data-dependent Grouping. CoRR abs/2006.14084 (2020) - [i10]Shashanka Ubaru, Lior Horesh, Guy Cohen:
Dynamic graph based epidemiological model for COVID-19 contact tracing data analysis and optimal testing prescription. CoRR abs/2009.04971 (2020) - [i9]Vassilis Kalantzis, Georgios Kollias, Shashanka Ubaru, Athanasios N. Nikolakopoulos, Lior Horesh, Kenneth L. Clarkson:
Projection techniques to update the truncated SVD of evolving matrices. CoRR abs/2010.06392 (2020)
2010 – 2019
- 2019
- [j5]Shashanka Ubaru, Yousef Saad:
Sampling and multilevel coarsening algorithms for fast matrix approximations. Numer. Linear Algebra Appl. 26(3) (2019) - [c10]Li Fan, David I Shuman, Shashanka Ubaru, Yousef Saad:
Spectrum-adapted Polynomial Approximation for Matrix Functions. ICASSP 2019: 4933-4937 - [c9]Shashanka Ubaru, Abd-Krim Seghouane, Yousef Saad:
Find the dimension that counts: Fast dimension estimation and Krylov PCA. SDM 2019: 720-728 - [i8]Osman Asif Malik, Shashanka Ubaru, Lior Horesh, Misha E. Kilmer, Haim Avron:
Tensor Graph Convolutional Networks for Prediction on Dynamic Graphs. CoRR abs/1910.07643 (2019) - 2018
- [c8]Cameron Musco, Praneeth Netrapalli, Aaron Sidford, Shashanka Ubaru, David P. Woodruff:
Spectrum Approximation Beyond Fast Matrix Multiplication: Algorithms and Hardness. ITCS 2018: 8:1-8:21 - [i7]Anastasios Kyrillidis, Shashanka Ubaru, Georgios Kollias, Kristofer E. Bouchard:
Run Procrustes, Run! On the convergence of accelerated Procrustes Flow. CoRR abs/1806.00534 (2018) - [i6]Li Fan, David I Shuman, Shashanka Ubaru, Yousef Saad:
Spectrum-Adapted Polynomial Approximation for Matrix Functions. CoRR abs/1808.09506 (2018) - [i5]Shashanka Ubaru, Abd-Krim Seghouane, Yousef Saad:
Find the dimension that counts: Fast dimension estimation and Krylov PCA. CoRR abs/1810.03733 (2018) - 2017
- [j4]Shashanka Ubaru, Abd-Krim Seghouane, Yousef Saad:
Improving the Incoherence of a Learned Dictionary via Rank Shrinkage. Neural Comput. 29(1): 263-285 (2017) - [j3]Shashanka Ubaru, Yousef Saad, Abd-Krim Seghouane:
Fast Estimation of Approximate Matrix Ranks Using Spectral Densities. Neural Comput. 29(5): 1317-1351 (2017) - [j2]Shashanka Ubaru, Jie Chen, Yousef Saad:
Fast Estimation of tr(f(A)) via Stochastic Lanczos Quadrature. SIAM J. Matrix Anal. Appl. 38(4): 1075-1099 (2017) - [j1]Shashanka Ubaru, Arya Mazumdar, Yousef Saad:
Low Rank Approximation and Decomposition of Large Matrices Using Error Correcting Codes. IEEE Trans. Inf. Theory 63(9): 5544-5558 (2017) - [c7]Shashanka Ubaru, Yousef Saad:
Applications of Trace Estimation Techniques. HPCSE 2017: 19-33 - [c6]Shashanka Ubaru, Arya Mazumdar:
Multilabel Classification with Group Testing and Codes. ICML 2017: 3492-3501 - [c5]Shashanka Ubaru, Kesheng Wu, Kristofer E. Bouchard:
UoI-NMF Cluster: A Robust Nonnegative Matrix Factorization Algorithm for Improved Parts-Based Decomposition and Reconstruction of Noisy Data. ICMLA 2017: 241-248 - [c4]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:
Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction. NIPS 2017: 1078-1086 - [i4]Cameron Musco, Praneeth Netrapalli, Aaron Sidford, Shashanka Ubaru, David P. Woodruff:
Spectrum Approximation Beyond Fast Matrix Multiplication: Algorithms and Hardness. CoRR abs/1704.04163 (2017) - [i3]Shashanka Ubaru, Yousef Saad:
Sampling and multilevel coarsening algorithms for fast matrix approximations. CoRR abs/1711.00439 (2017) - 2016
- [c3]Shashanka Ubaru, Yousef Saad:
Fast methods for estimating the Numerical rank of large matrices. ICML 2016: 468-477 - [c2]Shashanka Ubaru, Arya Mazumdar, Alexander Barg:
Group testing schemes from low-weight codewords of BCH codes. ISIT 2016: 2863-2867 - [i2]Shashanka Ubaru, Yousef Saad, Abd-Krim Seghouane:
Fast estimation of approximate matrix ranks using spectral densities. CoRR abs/1608.05754 (2016) - 2015
- [c1]Shashanka Ubaru, Arya Mazumdar, Yousef Saad:
Low Rank Approximation using Error Correcting Coding Matrices. ICML 2015: 702-710 - [i1]Shashanka Ubaru, Arya Mazumdar, Yousef Saad:
Low rank approximation and decomposition of large matrices using error correcting codes. CoRR abs/1512.09156 (2015)
Coauthor Index
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last updated on 2024-11-30 01:10 CET by the dblp team
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