Adam Dziedzic

CoRR, 2024

2023

Private Multi-Winner Voting for Machine Learning.

[BibT_eX]

[DOI]

Natalie Dullerud

Vinith M. Suriyakumar

Somesh Jha

Xiao Wang

Proc. Priv. Enhancing Technol., January, 2023

Individualized PATE: Differentially Private Machine Learning with Individual Privacy Guarantees.

[BibT_eX]

[DOI]

Proc. Priv. Enhancing Technol., January, 2023

Robust and Actively Secure Serverless Collaborative Learning.

[BibT_eX]

[DOI]

Olive Franzese

Mark R. Thomas

CoRR, 2023

Is Federated Learning a Practical PET Yet?

[BibT_eX]

[DOI]

Franziska Boenisch

Roei Schuster

Ilia Shumailov

CoRR, 2023

Robust and Actively Secure Serverless Collaborative Learning.

[BibT_eX]

[DOI]

Nicholas Franzese

Mark R. Thomas

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Flocks of Stochastic Parrots: Differentially Private Prompt Learning for Large Language Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Have it your way: Individualized Privacy Assignment for DP-SGD.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Reconstructing Individual Data Points in Federated Learning Hardened with Differential Privacy and Secure Aggregation.

[BibT_eX]

[DOI]

Franziska Boenisch

Roei Schuster

Ilia Shumailov

Proceedings of the 8th IEEE European Symposium on Security and Privacy, 2023

When the Curious Abandon Honesty: Federated Learning Is Not Private.

[BibT_eX]

[DOI]

Franziska Boenisch

Roei Schuster

Ilia Shumailov

Proceedings of the 8th IEEE European Symposium on Security and Privacy, 2023

2022

p-DkNN: Out-of-Distribution Detection Through Statistical Testing of Deep Representations.

[BibT_eX]

[DOI]

CoRR, 2022

Selective Classification Via Neural Network Training Dynamics.

[BibT_eX]

[DOI]

CoRR, 2022

Dataset Inference for Self-Supervised Models.

[BibT_eX]

[DOI]

Haonan Duan

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On the Difficulty of Defending Self-Supervised Learning against Model Extraction.

[BibT_eX]

[DOI]

Nikita Dhawan

Jonas Guan

Proceedings of the International Conference on Machine Learning, 2022

Increasing the Cost of Model Extraction with Calibrated Proof of Work.

[BibT_eX]

[DOI]

Yu Shen Lu

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

On the Exploitability of Audio Machine Learning Pipelines to Surreptitious Adversarial Examples.

[BibT_eX]

[DOI]

CoRR, 2021

CaPC Learning: Confidential and Private Collaborative Learning.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Machine Learning enabled Spectrum Sharing in Dense LTE-U/Wi-Fi Coexistence Scenarios.

[BibT_eX]

[DOI]

Vanlin Sathya

Muhammad Iqbal Rochman

Monisha Ghosh

Sanjay Krishnan

CoRR, 2020

An Empirical Evaluation of Perturbation-based Defenses.

[BibT_eX]

[DOI]

Sanjay Krishnan

CoRR, 2020

Machine Learning based detection of multiple Wi-Fi BSSs for LTE-U CSAT.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Computing, Networking and Communications, 2020

Pretrained Transformers Improve Out-of-Distribution Robustness.

[BibT_eX]

[DOI]

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Artificial Intelligence in Resource-Constrained and Shared Environments.

[BibT_eX]

[DOI]

ACM SIGOPS Oper. Syst. Rev., 2019

Band-limited Training and Inference for Convolutional Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

DeepLens: Towards a Visual Data Management System.

[BibT_eX]

[DOI]

Sanjay Krishnan

Aaron J. Elmore

Proceedings of the 9th Biennial Conference on Innovative Data Systems Research, 2019

2018

Columnstore and B+ tree - Are Hybrid Physical Designs Important?

[BibT_eX]

[DOI]

Proceedings of the 2018 International Conference on Management of Data, 2018

2017

BigDAWG Polystore Release and Demonstration.

[BibT_eX]

[DOI]

CoRR, 2017

Version 0.1 of the BigDAWG Polystore System.

[BibT_eX]

[DOI]

CoRR, 2017

BigDAWG version 0.1.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE High Performance Extreme Computing Conference, 2017

Demonstrating the BigDAWG Polystore System for Ocean Metagenomics Analysis.

[BibT_eX]

[DOI]

Proceedings of the 8th Biennial Conference on Innovative Data Systems Research, 2017

2016

DBMS Data Loading: An Analysis on Modern Hardware.

[BibT_eX]

[DOI]

Proceedings of the Data Management on New Hardware, 2016

Integrating real-time and batch processing in a polystore.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE High Performance Extreme Computing Conference, 2016

Data transformation and migration in polystores.

[BibT_eX]

[DOI]