Kevin Shi

According to our database, Kevin Shi authored at least 11 papers between 2017 and 2023.

Collaborative distances:

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

2023

Evaluating Permissioned Blockchain Using Stochastic Modeling and Chaos Engineering.

Shiv Sondhi, Sherif Saad, Kevin Shi, Mohammad Saiful Islam Mamun, Issa Traoré

CoRR, 2023

Automated Feature Engineering for AutoML Using Genetic Algorithms.

Kevin Shi, Sherif Saad

Proceedings of the 20th International Conference on Security and Cryptography, 2023

2021

DeepTaskAPT: Insider APT detection using Task-tree based Deep Learning.

Mohammad Mamun, Kevin Shi

Proceedings of the 20th IEEE International Conference on Trust, 2021

Surprisingly Popular Voting Recovers Rankings, Surprisingly!

Hadi Hosseini, Debmalya Mandal, Nisarg Shah, Kevin Shi

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Chaos Engineering For Understanding Consensus Algorithms Performance in Permissioned Blockchains.

Shiv Sondhi, Sherif Saad, Kevin Shi, Mohammad Mamun, Issa Traoré

Proceedings of the IEEE Intl Conf on Dependable, 2021

2020

Cryptographic approaches to security and optimization in machine learning.

Kevin Shi

PhD thesis, 2020

2019

In Pursuit of Clarity In Obfuscation.

Allison Bishop, Lucas Kowalczyk, Tal Malkin, Valerio Pastro, Mariana Raykova, Kevin Shi

IACR Cryptol. ePrint Arch., 2019

A cryptographic approach to black box adversarial machine learning.

Kevin Shi, Daniel Hsu, Allison Bishop

CoRR, 2019

2018

A Simple Obfuscation Scheme for Pattern-Matching with Wildcards.

Allison Bishop, Lucas Kowalczyk, Tal Malkin, Valerio Pastro, Mariana Raykova, Kevin Shi

IACR Cryptol. ePrint Arch., 2018

2017

Linear regression without correspondence.

Daniel J. Hsu, Kevin Shi, Xiaorui Sun

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Correspondence retrieval.

Alexandr Andoni, Daniel J. Hsu, Kevin Shi, Xiaorui Sun

Proceedings of the 30th Conference on Learning Theory, 2017