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Sanghamitra Dutta
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引用次数
引用次数
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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
4102016
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
2722019
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
International conference on artificial intelligence and statistics, 803-812, 2018
1812018
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
1572020
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
1522017
A unified coded deep neural network training strategy based on generalized polydot codes
S Dutta, Z Bai, H Jeong, TM Low, P Grover
2018 IEEE International Symposium on Information Theory (ISIT), 1585-1589, 2018
1132018
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
862017
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
442018
Robust counterfactual explanations for tree-based ensembles
S Dutta, J Long, S Mishra, C Tilli, D Magazzeni
International conference on machine learning, 5742-5756, 2022
372022
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
322021
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
322021
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
292020
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
272019
Information flow in computational systems
P Venkatesh, S Dutta, P Grover
IEEE Transactions on Information Theory 66 (9), 5456-5491, 2020
212020
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
182020
Robust counterfactual explanations for neural networks with probabilistic guarantees
F Hamman, E Noorani, S Mishra, D Magazzeni, S Dutta
International Conference on Machine Learning, 12351-12367, 2023
172023
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
132021
GTN-ED: Event detection using graph transformer networks
S Dutta, L Ma, TK Saha, D Lu, J Tetreault, A Jaimes
arXiv preprint arXiv:2104.15104, 2021
102021
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
92019
Monopoly: Financial prediction from monetary policy conference videos using multimodal cues
P Mathur, A Neerkaje, M Chhibber, R Sawhney, F Guo, F Dernoncourt, ...
Proceedings of the 30th ACM International Conference on Multimedia, 2276-2285, 2022
82022
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