Zahra Ghodsi

According to our database, Zahra Ghodsi authored at least 19 papers between 2017 and 2023.

Collaborative distances:

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

2023

AnoFel: Supporting Anonymity for Privacy-Preserving Federated Learning.

Ghada Almashaqbeh, Zahra Ghodsi

CoRR, 2023

zPROBE: Zero Peek Robustness Checks for Federated Learning.

Zahra Ghodsi, Mojan Javaheripi, Nojan Sheybani, Xinqiao Zhang, Ke Huang, Farinaz Koushanfar

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

AdaGL: Adaptive Learning for Agile Distributed Training of Gigantic GNNs.

Ruisi Zhang, Mojan Javaheripi, Zahra Ghodsi, Amit Bleiweiss, Farinaz Koushanfar

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

ZKROWNN: Zero Knowledge Right of Ownership for Neural Networks.

Nojan Sheybani, Zahra Ghodsi, Ritvik Kapila, Farinaz Koushanfar

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

Characterizing and Optimizing End-to-End Systems for Private Inference.

Karthik Garimella, Zahra Ghodsi, Nandan Kumar Jha, Siddharth Garg, Brandon Reagen

Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023

2022

Sphynx: A Deep Neural Network Design for Private Inference.

Minsu Cho, Zahra Ghodsi, Brandon Reagen, Siddharth Garg, Chinmay Hegde

IEEE Secur. Priv., 2022

2021

CryptoNite: Revealing the Pitfalls of End-to-End Private Inference at Scale.

Karthik Garimella, Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen

CoRR, 2021

Sphynx: ReLU-Efficient Network Design for Private Inference.

Minsu Cho, Zahra Ghodsi, Brandon Reagen, Siddharth Garg, Chinmay Hegde

CoRR, 2021

Circa: Stochastic ReLUs for Private Deep Learning.

Zahra Ghodsi, Nandan Kumar Jha, Brandon Reagen, Siddharth Garg

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles.

Zahra Ghodsi, Siva Kumar Sastry Hari, Iuri Frosio, Timothy Tsai, Alejandro J. Troccoli, Stephen W. Keckler, Siddharth Garg, Anima Anandkumar

Proceedings of the IEEE Intelligent Vehicles Symposium, 2021

DeepReDuce: ReLU Reduction for Fast Private Inference.

Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Enabling Timing Error Resilience for Low-Power Systolic-Array Based Deep Learning Accelerators.

Jeff Zhang, Zahra Ghodsi, Siddharth Garg, Kartheek Rangineni

IEEE Des. Test, 2020

SafeTPU: A Verifiably Secure Hardware Accelerator for Deep Neural Networks.

Maria I. Mera Collantes, Zahra Ghodsi, Siddharth Garg

Proceedings of the 38th IEEE VLSI Test Symposium, 2020

CryptoNAS: Private Inference on a ReLU Budget.

Zahra Ghodsi, Akshaj Kumar Veldanda, Brandon Reagen, Siddharth Garg

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2018

Outsourcing Private Machine Learning via Lightweight Secure Arithmetic Computation.

Siddharth Garg, Zahra Ghodsi, Carmit Hazay, Yuval Ishai, Antonio Marcedone, Muthuramakrishnan Venkitasubramaniam

CoRR, 2018

ThUnderVolt: Enabling Aggressive Voltage Underscaling and Timing Error Resilience for Energy Efficient Deep Neural Network Accelerators.

Jeff Zhang, Kartheek Rangineni, Zahra Ghodsi, Siddharth Garg

CoRR, 2018

Thundervolt: enabling aggressive voltage underscaling and timing error resilience for energy efficient deep learning accelerators.

Jeff Zhang, Kartheek Rangineni, Zahra Ghodsi, Siddharth Garg

Proceedings of the 55th Annual Design Automation Conference, 2018

2017

SafetyNets: Verifiable Execution of Deep Neural Networks on an Untrusted Cloud.

Zahra Ghodsi, Tianyu Gu, Siddharth Garg

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

Optimal checkpointing for secure intermittently-powered IoT devices.

Zahra Ghodsi, Siddharth Garg, Ramesh Karri

Proceedings of the 2017 IEEE/ACM International Conference on Computer-Aided Design, 2017