research
∙
07/27/2023
Samplable Anonymous Aggregation for Private Federated Data Analysis
We revisit the problem of designing scalable protocols for private stati...
share
research
∙
07/14/2023
Population Expansion for Training Language Models with Private Federated Learning
Federated learning (FL) combined with differential privacy (DP) offers m...
research
∙
11/18/2022
Private Federated Statistics in an Interactive Setting
Privately learning statistics of events on devices can enable improved u...
research
∙
07/18/2022
FLAIR: Federated Learning Annotated Image Repository
Cross-device federated learning is an emerging machine learning (ML) par...
research
∙
03/15/2022
Training a Tokenizer for Free with Private Federated Learning
Federated learning with differential privacy, i.e. private federated lea...
research
∙
11/09/2020
Adversarial Semantic Collisions
We study semantic collisions: texts that are semantically unrelated but ...
research
∙
07/05/2020
You Autocomplete Me: Poisoning Vulnerabilities in Neural Code Completion
Code autocompletion is an integral feature of modern code editors and ID...
research
∙
03/31/2020
Information Leakage in Embedding Models
Embeddings are functions that map raw input data to low-dimensional vect...
research
∙
09/28/2019
Generalized Zero-shot ICD Coding
The International Classification of Diseases (ICD) is a list of classifi...
research
∙
09/27/2019
Membership Encoding for Deep Learning
Machine learning as a service (MLaaS), and algorithm marketplaces are on...
research
∙
05/28/2019
Overlearning Reveals Sensitive Attributes
`Overlearning' means that a model trained for a seemingly simple objecti...
research
∙
11/01/2018
The Natural Auditor: How To Tell If Someone Used Your Words To Train Their Model
To help enforce data-protection regulations such as GDPR and detect unau...
research
∙
05/10/2018
Inference Attacks Against Collaborative Learning
Collaborative machine learning and related techniques such as distribute...
research
∙
03/15/2018
Chiron: Privacy-preserving Machine Learning as a Service
Major cloud operators offer machine learning (ML) as a service, enabling...
research
∙
02/15/2018
Fooling OCR Systems with Adversarial Text Images
We demonstrate that state-of-the-art optical character recognition (OCR)...
research
∙
01/31/2018
Kernel Distillation for Gaussian Processes
Gaussian processes (GPs) are flexible models that can capture complex st...
research
∙
10/18/2016
Membership Inference Attacks against Machine Learning Models
We quantitatively investigate how machine learning models leak informati...
research
∙
09/27/2016
