Membership inference attacks on machine learning: A survey
Machine learning (ML) models have been widely applied to various applications, including
image classification, text generation, audio recognition, and graph data analysis. However …
image classification, text generation, audio recognition, and graph data analysis. However …
Recommender systems in the era of large language models (llms)
With the prosperity of e-commerce and web applications, Recommender Systems (RecSys)
have become an important component of our daily life, providing personalized suggestions …
have become an important component of our daily life, providing personalized suggestions …
Trustworthy ai: From principles to practices
The rapid development of Artificial Intelligence (AI) technology has enabled the deployment
of various systems based on it. However, many current AI systems are found vulnerable to …
of various systems based on it. However, many current AI systems are found vulnerable to …
A comprehensive survey on trustworthy graph neural networks: Privacy, robustness, fairness, and explainability
Graph Neural Networks (GNNs) have made rapid developments in the recent years. Due to
their great ability in modeling graph-structured data, GNNs are vastly used in various …
their great ability in modeling graph-structured data, GNNs are vastly used in various …
The next frontier: AI we can really trust
A Holzinger - Joint European conference on machine learning and …, 2021 - Springer
Enormous advances in the domain of statistical machine learning, the availability of large
amounts of training data, and increasing computing power have made Artificial Intelligence …
amounts of training data, and increasing computing power have made Artificial Intelligence …
Trustworthy graph neural networks: Aspects, methods and trends
Graph neural networks (GNNs) have emerged as a series of competent graph learning
methods for diverse real-world scenarios, ranging from daily applications like …
methods for diverse real-world scenarios, ranging from daily applications like …
Towards trustworthy energy disaggregation: A review of challenges, methods, and perspectives for non-intrusive load monitoring
Non-intrusive load monitoring (NILM) is the task of disaggregating the total power
consumption into its individual sub-components. Over the years, signal processing and …
consumption into its individual sub-components. Over the years, signal processing and …
Trustworthy federated learning via blockchain
The safety-critical scenarios of artificial intelligence (AI), such as autonomous driving,
Internet of Things, smart healthcare, etc., have raised critical requirements of trustworthy AI …
Internet of Things, smart healthcare, etc., have raised critical requirements of trustworthy AI …
[HTML][HTML] A survey on fairness-aware recommender systems
As information filtering services, recommender systems have extremely enriched our daily
life by providing personalized suggestions and facilitating people in decision-making, which …
life by providing personalized suggestions and facilitating people in decision-making, which …