Sanghamitra Dutta

According to our database1, Sanghamitra Dutta authored at least 20 papers between 2014 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2020
Information Flow in Computational Systems.
IEEE Trans. Inf. Theory, 2020

On the Optimal Recovery Threshold of Coded Matrix Multiplication.
IEEE Trans. Inf. Theory, 2020

Addressing Unreliability in Emerging Devices and Non-von Neumann Architectures Using Coded Computing.
Proc. IEEE, 2020

Fairness Under Feature Exemptions: Counterfactual and Observational Measures.
CoRR, 2020

Slow and Stale Gradients Can Win the Race.
CoRR, 2020

How else can we define Information Flow in Neural Circuits?
Proceedings of the IEEE International Symposium on Information Theory, 2020

Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing.
Proceedings of the 37th International Conference on Machine Learning, 2020

An Information-Theoretic Quantification of Discrimination with Exempt Features.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
"Short-Dot": Computing Large Linear Transforms Distributedly Using Coded Short Dot Products.
IEEE Trans. Inf. Theory, 2019

An Information-Theoretic Perspective on the Relationship Between Fairness and Accuracy.
CoRR, 2019

CodeNet: Training Large Scale Neural Networks in Presence of Soft-Errors.
CoRR, 2019

How should we define Information Flow in Neural Circuits?
Proceedings of the IEEE International Symposium on Information Theory, 2019

2018
A Unified Coded Deep Neural Network Training Strategy Based on Generalized PolyDot Codes for Matrix Multiplication.
CoRR, 2018

A Unified Coded Deep Neural Network Training Strategy based on Generalized PolyDot codes.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

An Application of Storage-Optimal MatDot Codes for Coded Matrix Multiplication: Fast k-Nearest Neighbors Estimation.
Proceedings of the IEEE International Conference on Big Data, 2018

Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Coded convolution for parallel and distributed computing within a deadline.
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

2016
Adaptivity provably helps: information-theoretic limits on $l_0$ cost of non-adaptive sensing.
CoRR, 2016

Adaptivity provably helps: Information-theoretic limits on l0 cost of non-adaptive sensing.
Proceedings of the IEEE International Symposium on Information Theory, 2016

2014
LAMP: A Locally Adapting Matching Pursuit Framework for Group Sparse Signatures in Ultra-Wide Band Radar Imaging.
CoRR, 2014


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