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Sanghamitra Dutta
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Short-dot: Computing large linear transforms distributedly using coded short dot products
S Dutta, V Cadambe, P Grover
Advances In Neural Information Processing Systems 29, 2016
3432016
On the optimal recovery threshold of coded matrix multiplication
S Dutta, M Fahim, F Haddadpour, H Jeong, V Cadambe, P Grover
IEEE Transactions on Information Theory 66 (1), 278-301, 2019
1932019
On the optimal recovery threshold of coded matrix multiplication
S Dutta, M Fahim, F Haddadpour, H Jeong, V Cadambe, P Grover
IEEE Transactions on Information Theory, 2019
1932019
Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD
S Dutta, G Joshi, S Ghosh, P Dube, P Nagpurkar
arXiv preprint arXiv:1803.01113, 2018
1452018
Coded convolution for parallel and distributed computing within a deadline
S Dutta, V Cadambe, P Grover
2017 IEEE International Symposium on Information Theory (ISIT), 2403-2407, 2017
1252017
A Unified Coded Deep Neural Network Training Strategy Based on Generalized PolyDot Codes for Matrix Multiplication
S Dutta, Z Bai, H Jeong, TM Low, P Grover
arXiv preprint arXiv:1811.10751, 2018
892018
On the optimal recovery threshold of coded matrix multiplication
M Fahim, H Jeong, F Haddadpour, S Dutta, V Cadambe, P Grover
2017 55th Annual Allerton Conference on Communication, Control, and …, 2017
752017
Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing
S Dutta, D Wei, H Yueksel, PY Chen, S Liu, KR Varshney
International Conference on Machine Learning, 2020
64*2020
An application of storage-optimal matdot codes for coded matrix multiplication: Fast k-nearest neighbors estimation
U Sheth, S Dutta, M Chaudhari, H Jeong, Y Yang, J Kohonen, T Roos, ...
2018 IEEE International Conference on Big Data (Big Data), 1113-1120, 2018
382018
CodeNet: Training large scale neural networks in presence of soft-errors
S Dutta, Z Bai, TM Low, P Grover
arXiv preprint arXiv:1903.01042, 2019
202019
An information-theoretic quantification of discrimination with exempt features
S Dutta, P Venkatesh, P Mardziel, A Datta, P Grover
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3825-3833, 2020
182020
Information flow in computational systems
P Venkatesh, S Dutta, P Grover
IEEE Transactions on Information Theory 66 (9), 5456-5491, 2020
162020
A survey on the robustness of feature importance and counterfactual explanations
S Mishra, S Dutta, J Long, D Magazzeni
arXiv preprint arXiv:2111.00358, 2021
92021
Addressing unreliability in emerging devices and Non-Von Neumann architectures using coded computing
S Dutta, H Jeong, Y Yang, V Cadambe, TM Low, P Grover
Proceedings of the IEEE 108 (8), 1219-1234, 2020
82020
How should we define information flow in neural circuits?
P Venkatesh, S Dutta, P Grover
2019 IEEE international symposium on information theory (ISIT), 176-180, 2019
82019
How else can we define Information Flow in Neural Circuits?
P Venkatesh, S Dutta, P Grover
2020 IEEE International Symposium on Information Theory (ISIT), 2879-2884, 2020
72020
Slow and stale gradients can win the race
S Dutta, J Wang, G Joshi
IEEE Journal on Selected Areas in Information Theory 2 (3), 1012-1024, 2021
62021
Fairness under feature exemptions: Counterfactual and observational measures
S Dutta, P Venkatesh, P Mardziel, A Datta, P Grover
IEEE Transactions on Information Theory 67 (10), 6675-6710, 2021
42021
Sparse Ultra Wide Band Radar imaging in a locally adapting matching pursuit (LAMP) framework
S Dutta, A De
2015 IEEE Radar Conference (RadarCon), 1216-1221, 2015
32015
LAMP: A Locally Adapting Matching Pursuit Framework for Group Sparse Signatures in Ultra-Wide Band Radar Imaging
S Dutta, A De
arXiv preprint arXiv:1411.4020, 2014
32014
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