A survey of algorithmic recourse: contrastive explanations and consequential recommendations
Machine learning is increasingly used to inform decision making in sensitive situations
where decisions have consequential effects on individuals' lives. In these settings, in …
where decisions have consequential effects on individuals' lives. In these settings, in …
Machine learning for healthcare wearable devices: the big picture
Using artificial intelligence and machine learning techniques in healthcare applications has
been actively researched over the last few years. It holds promising opportunities as it is …
been actively researched over the last few years. It holds promising opportunities as it is …
I know what you trained last summer: A survey on stealing machine learning models and defences
Machine-Learning-as-a-Service (MLaaS) has become a widespread paradigm, making
even the most complex Machine Learning models available for clients via, eg, a pay-per …
even the most complex Machine Learning models available for clients via, eg, a pay-per …
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects
Machine learning is increasingly used to inform decision-making in sensitive situations
where decisions have consequential effects on individuals' lives. In these settings, in …
where decisions have consequential effects on individuals' lives. In these settings, in …
MP2ML: A mixed-protocol machine learning framework for private inference
Privacy-preserving machine learning (PPML) has many applications, from medical image
classification and anomaly detection to financial analysis. nGraph-HE enables data …
classification and anomaly detection to financial analysis. nGraph-HE enables data …
[HTML][HTML] Adversarial machine learning in industry: A systematic literature review
Abstract Adversarial Machine Learning (AML) discusses the act of attacking and defending
Machine Learning (ML) Models, an essential building block of Artificial Intelligence (AI). ML …
Machine Learning (ML) Models, an essential building block of Artificial Intelligence (AI). ML …
Secure and trustworthy artificial intelligence-extended reality (AI-XR) for metaverses
Metaverse is expected to emerge as a new paradigm for the next-generation Internet,
providing fully immersive and personalized experiences to socialize, work, and play in self …
providing fully immersive and personalized experiences to socialize, work, and play in self …
Generating robust dnn with resistance to bit-flip based adversarial weight attack
Rowhammer Attack, a new DRAM-based attack, was developed exploiting weak cells to
alter their content. Such attacks can be launched at the user level without requiring access …
alter their content. Such attacks can be launched at the user level without requiring access …
Securing machine learning in the cloud: A systematic review of cloud machine learning security
With the advances in machine learning (ML) and deep learning (DL) techniques, and the
potency of cloud computing in offering services efficiently and cost-effectively, Machine …
potency of cloud computing in offering services efficiently and cost-effectively, Machine …
A blockchain-enabled explainable federated learning for securing internet-of-things-based social media 3.0 networks
Social media (SM) 3.0 integrates SM platforms, such as Facebook and Twitter, with the
Internet of Things (IoT), and has a great potential to change how we interact with mobile …
Internet of Things (IoT), and has a great potential to change how we interact with mobile …