Matthew Sotoudeh

According to our database, Matthew Sotoudeh authored at least 13 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Sidekick: In-Network Assistance for Secure End-to-End Transport Protocols.

Gina Yuan, Matthew Sotoudeh, David K. Zhang, Michael Welzl, David Mazières, Keith Winstein

Proceedings of the 21st USENIX Symposium on Networked Systems Design and Implementation, 2024

2023

SyReNN: A tool for analyzing deep neural networks.

Matthew Sotoudeh, Zhe Tao, Aditya V. Thakur

Int. J. Softw. Tools Technol. Transf., April, 2023

2022

System-Specific Interpreters Make Megasystems Friendlier.

Matthew Sotoudeh

CoRR, 2022

Sidecar: in-network performance enhancements in the age of paranoid transport protocols.

Gina Yuan, David K. Zhang, Matthew Sotoudeh, Michael Welzl, Keith Winstein

Proceedings of the 21st ACM Workshop on Hot Topics in Networks, 2022

2021

SyReNN: A Tool for Analyzing Deep Neural Networks.

Matthew Sotoudeh, Aditya V. Thakur

Proceedings of the Tools and Algorithms for the Construction and Analysis of Systems, 2021

Provable repair of deep neural networks.

Matthew Sotoudeh, Aditya V. Thakur

Proceedings of the PLDI '21: 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation, 2021

2020

Abstract Neural Networks.

Matthew Sotoudeh, Aditya V. Thakur

Proceedings of the Static Analysis - 27th International Symposium, 2020

Analogy-making as a Core primitive in the software engineering toolbox.

Matthew Sotoudeh, Aditya V. Thakur

Proceedings of the 2020 ACM SIGPLAN International Symposium on New Ideas, 2020

2019

A Symbolic Neural Network Representation and its Application to Understanding, Verifying, and Patching Networks.

Matthew Sotoudeh, Aditya V. Thakur

CoRR, 2019

Computing Linear Restrictions of Neural Networks.

Matthew Sotoudeh, Aditya V. Thakur

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

C3-Flow: Compute Compression Co-Design Flow for Deep Neural Networks.

Matthew Sotoudeh, Sara S. Baghsorkhi

Proceedings of the 56th Annual Design Automation Conference 2019, 2019

ISA mapper: a compute and hardware agnostic deep learning compiler.

Matthew Sotoudeh, Anand Venkat, Michael J. Anderson, Evangelos Georganas, Alexander Heinecke, Jason Knight

Proceedings of the 16th ACM International Conference on Computing Frontiers, 2019

2018

DeepThin: A Self-Compressing Library for Deep Neural Networks.

Matthew Sotoudeh, Sara S. Baghsorkhi

CoRR, 2018