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06/08/2023
Re-aligning Shadow Models can Improve White-box Membership Inference Attacks
Machine learning models have been shown to leak sensitive information ab...
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02/02/2023
On the Efficacy of Differentially Private Few-shot Image Classification
There has been significant recent progress in training differentially pr...
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02/01/2023
Analyzing Leakage of Personally Identifiable Information in Language Models
Language Models (LMs) have been shown to leak information about training...
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10/04/2022
Invariant Aggregator for Defending Federated Backdoor Attacks
Federated learning is gaining popularity as it enables training of high-...
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09/18/2022
Membership Inference Attacks and Generalization: A Causal Perspective
Membership inference (MI) attacks highlight a privacy weakness in presen...
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09/18/2022
Distribution inference risks: Identifying and mitigating sources of leakage
A large body of work shows that machine learning (ML) models can leak se...
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06/10/2022
Bayesian Estimation of Differential Privacy
Algorithms such as Differentially Private SGD enable training machine le...
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10/07/2021
The Connection between Out-of-Distribution Generalization and Privacy of ML Models
With the goal of generalizing to out-of-distribution (OOD) data, recent ...
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07/25/2020
SOTERIA: In Search of Efficient Neural Networks for Private Inference
ML-as-a-service is gaining popularity where a cloud server hosts a train...
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06/25/2020
Replication-Robust Payoff-Allocation with Applications in Machine Learning Marketplaces
The ever-increasing take-up of machine learning techniques requires ever...
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06/12/2020
Domain Generalization using Causal Matching
Learning invariant representations has been proposed as a key technique ...
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06/12/2020
Dataset-Level Attribute Leakage in Collaborative Learning
Multi-party machine learning allows several parties to build a joint mod...
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04/05/2020
FALCON: Honest-Majority Maliciously Secure Framework for Private Deep Learning
This paper aims to enable training and inference of neural networks in a...
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01/08/2020
To Transfer or Not to Transfer: Misclassification Attacks Against Transfer Learned Text Classifiers
Transfer learning — transferring learned knowledge — has brought a parad...
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12/17/2019
Analyzing Privacy Loss in Updates of Natural Language Models
To continuously improve quality and reflect changes in data, machine lea...
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12/05/2019
On the Intrinsic Privacy of Stochastic Gradient Descent
Private learning algorithms have been proposed that ensure strong differ...
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11/08/2019
Collaborative Machine Learning Markets with Data-Replication-Robust Payments
We study the problem of collaborative machine learning markets where mul...
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09/27/2019
Alleviating Privacy Attacks via Causal Learning
Machine learning models, especially deep neural networks have been shown...
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10/01/2018