Vertical federated learning: Concepts, advances, and challenges
Vertical Federated Learning (VFL) is a federated learning setting where multiple parties with
different features about the same set of users jointly train machine learning models without …
different features about the same set of users jointly train machine learning models without …
A robust analysis of adversarial attacks on federated learning environments
Federated Learning is a growing branch of Artificial Intelligence with the wide usage of
mobile computing and IoT technologies. Since this technology uses distributed computing …
mobile computing and IoT technologies. Since this technology uses distributed computing …
Using highly compressed gradients in federated learning for data reconstruction attacks
Federated learning (FL) preserves data privacy by exchanging gradients instead of local
training data. However, these private data can still be reconstructed from the exchanged …
training data. However, these private data can still be reconstructed from the exchanged …
A survey on vertical federated learning: From a layered perspective
Vertical federated learning (VFL) is a promising category of federated learning for the
scenario where data is vertically partitioned and distributed among parties. VFL enriches the …
scenario where data is vertically partitioned and distributed among parties. VFL enriches the …
Fedads: A benchmark for privacy-preserving cvr estimation with vertical federated learning
Conversion rate (CVR) estimation aims to predict the probability of conversion event after a
user has clicked an ad. Typically, online publisher has user browsing interests and click …
user has clicked an ad. Typically, online publisher has user browsing interests and click …
Advancements in federated learning: Models, methods, and privacy
Federated learning (FL) is a promising technique for resolving the rising privacy and security
concerns. Its main ingredient is to cooperatively learn the model among the distributed …
concerns. Its main ingredient is to cooperatively learn the model among the distributed …
Label leakage and protection from forward embedding in vertical federated learning
Vertical federated learning (vFL) has gained much attention and been deployed to solve
machine learning problems with data privacy concerns in recent years. However, some …
machine learning problems with data privacy concerns in recent years. However, some …
Hashvfl: Defending against data reconstruction attacks in vertical federated learning
Vertical Federated Learning (VFL) is a trending collaborative machine learning model
training solution. Existing industrial frameworks employ secure multi-party computation …
training solution. Existing industrial frameworks employ secure multi-party computation …
Differentially private vertical federated learning
A successful machine learning (ML) algorithm often relies on a large amount of high-quality
data to train well-performed models. Supervised learning approaches, such as deep …
data to train well-performed models. Supervised learning approaches, such as deep …
All you need is hashing: Defending against data reconstruction attack in vertical federated learning
Vertical federated learning is a trending solution for multi-party collaboration in training
machine learning models. Industrial frameworks adopt secure multi-party computation …
machine learning models. Industrial frameworks adopt secure multi-party computation …