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Aritra Dutta
Aritra Dutta
Assistant Professor, Dept. of Mathematics and Computer Science, University of Southern Denmark
Verified email at sdu.dk - Homepage
Title
Cited by
Cited by
Year
On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning
A Dutta, EH Bergou, AM Abdelmoniem, CY Ho, AN Sahu, M Canini, ...
AAAI-20 - Thirty-fourth AAAI Conference on Artificial Intelligence 34 (4 …, 2020
732020
GRACE: A compressed communication framework for distributed machine learning
H Xu, CY Ho, AM Abdelmoniem, A Dutta, EH Bergou, K Karatsenidis, ...
2021 IEEE 41st International Conference on Distributed Computing Systems …, 2021
532021
Compressed communication for distributed deep learning: Survey and quantitative evaluation
H Xu, CY Ho, AM Abdelmoniem, A Dutta, EH Bergou, K Karatsenidis, ...
522020
Deepreduce: A sparse-tensor communication framework for federated deep learning
H Xu, K Kostopoulou, A Dutta, X Li, A Ntoulas, P Kalnis
Advances in Neural Information Processing Systems 34, 21150-21163, 2021
23*2021
Fast Detection of Compressively-Sensed IR Targets Using Stochastically Trained Least Squares and Compressed Quadratic Correlation Filters
B Millikan, A Dutta, Q Sun, H Foroosh
IEEE Transactions on Aerospace and Electronic Systems 53 (5), 2449-2461, 2017
23*2017
Rethinking gradient sparsification as total error minimization
A Sahu, A Dutta, A M Abdelmoniem, T Banerjee, M Canini, P Kalnis
Advances in Neural Information Processing Systems 34, 8133-8146, 2021
222021
A Nonconvex Projection Method for Robust PCA
A Dutta, F Hanzely, P Richtárik
AAAI-19 - Thirty-Third AAAI Conference on Artificial Intelligence, 2019
202019
On a Problem of Weighted Low Rank Approximation of Matrices
A Dutta, X Li
SIAM Journal on Matrix Analysis and Applications 38 (2), 530-553, 2017
192017
Initialized Iterative Reweighted Least Squares for Automatic Target Recognition
B Millikan, A Dutta, N Rahnavard, Q Sun, H Foroosh
MILCOM 2015 - In proceedings of IEEE Military Communications Conference 2015 …, 2015
182015
Huffman Coding Based Encoding Techniques for Fast Distributed Deep Learning
RR Gajjala, S Banchhor, AM Abdelmoniem, A Dutta, M Canini, P Kalnis
Proceedings of ACM CoNEXT'20: 1st Workshop on Distributed Machine Learning …, 2020
172020
Direct Nonlinear Acceleration
A Dutta, EH Bergou, Y Xiao, M Canini, P Richtárik
EURO Journal on Computational Optimization 10, 2022
16*2022
Weighted Singular Value Thresholding and its Applications to Background Estimation
A Dutta, B Gong, X Li, M Shah
142017
Weighted low-rank approximation of matrices and background modeling
A Dutta, X Li, P Richtárik
arXiv preprint arXiv:1804.06252, 2018
122018
Weighted low rank approximation for background estimation problems
A Dutta, X Li
ICCVW-2017-IEEE International Conference on Computer Vision Workshops (ICCVW), 2017
122017
A Batch-Incremental Video Background Estimation Model using Weighted Low-Rank Approximation of Matrices
A Dutta, X Li, P Richtarik
ICCVW 2017- IEEE International Conference on Computer Vision Workshops (ICCVW), 2017
112017
Weighted Low-Rank Approximation of Matrices: Some Analytical and Numerical Aspects
A Dutta
Ph.D. Dissertation, Department of Mathematics, University of Central Florida., 2017
112017
A Fast Algorithm for a Weighted Low-Rank Approximation
A Dutta, X Li
International Association for Pattern Recognition (IAPR) conference on …, 2017
112017
Shrinkage Function And Its Applications In Matrix Approximation
T Boas, A Dutta, X Li, K Mercier, E Niderman
Electronic Journal of Linear Algebra 32, 163–171, 2017
112017
Best pair formulation & accelerated scheme for non-convex principal component pursuit
A Dutta, F Hanzely, J Liang, P Richtárik
IEEE Transactions on Signal Processing, 2020
62020
Online and Batch Supervised Background Estimation via L1 Regression
A Dutta, P Richtarik
WACV 2019 – IEEE Winter Conference on the Applications of Computer Vision …, 2019
62019
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