Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Ren, Hanchi"'
Unmanned Aerial Vehicle (UAV) swarms are increasingly deployed in dynamic, data-rich environments for applications such as environmental monitoring and surveillance. These scenarios demand efficient data processing while maintaining privacy and secur
Externí odkaz:
http://arxiv.org/abs/2410.15882
Reliable object grasping is one of the fundamental tasks in robotics. However, determining grasping pose based on single-image input has long been a challenge due to limited visual information and the complexity of real-world objects. In this paper,
Externí odkaz:
http://arxiv.org/abs/2410.15879
Vision-Language Models (VLMs) play a crucial role in robotic manipulation by enabling robots to understand and interpret the visual properties of objects and their surroundings, allowing them to perform manipulation based on this multimodal understan
Externí odkaz:
http://arxiv.org/abs/2410.15863
Federated learning (FL) is a powerful Machine Learning (ML) paradigm that enables distributed clients to collaboratively learn a shared global model while keeping the data on the original device, thereby preserving privacy. A central challenge in FL
Externí odkaz:
http://arxiv.org/abs/2404.15919
This review paper takes a comprehensive look at malicious attacks against FL, categorizing them from new perspectives on attack origins and targets, and providing insights into their methodology and impact. In this survey, we focus on threat models t
Externí odkaz:
http://arxiv.org/abs/2311.16065
Federated Learning (FL) is a widely adopted privacy-preserving machine learning approach where private data remains local, enabling secure computations and the exchange of local model gradients between local clients and third-party parameter servers.
Externí odkaz:
http://arxiv.org/abs/2305.04095
Publikováno v:
In Neurocomputing 7 March 2024 573
Publikováno v:
ACM Transactions on Intelligent Systems and Technology (TIST), 2022
Data privacy has become an increasingly important issue in Machine Learning (ML), where many approaches have been developed to tackle this challenge, e.g. cryptography (Homomorphic Encryption (HE), Differential Privacy (DP), etc.) and collaborative t
Externí odkaz:
http://arxiv.org/abs/2105.00529
Publikováno v:
In Neurocomputing 7 February 2024 569
Typical machine learning approaches require centralized data for model training, which may not be possible where restrictions on data sharing are in place due to, for instance, privacy and gradient protection. The recently proposed Federated Learning
Externí odkaz:
http://arxiv.org/abs/2007.07296