Add to ORKGFederated Learning (FL)[1] is a type of distributed machine learning that allows the owners of the training data to preserve their privacy while still be- ing able to collectively train a model. FL is a new area in research and several chal- lenges reagarding privacy and communication cost still need to be overcome. Gradient leakage[1], for example is the possibility of partially reconstruct- ing the private data of a participant based on the weight gradients they send over the network dur- ing FL, which poses a great risk for privacy. Miti- gations against this problem lead to an increase in the computational complexity of the scheme or af- fect the performance of the resulting fully trained model. Other issues regarding trusting the centr...
The advance of Machine Learning (ML) techniques has become the driving force in the development of A...
The advent of machine learning techniques has given rise to modern devices with built-in models for ...
To preserve participants' privacy, Federated Learning (FL) has been proposed to let participants col...
Federated Learning starts to give a new perspective regarding the applicability of machine learning ...
Federated learning (FL) is a new paradigm that allows several parties to train a model together with...
A possible approach to address the increasing security and privacy concerns is federated learning (F...
Federated learning is an improved version of distributed machine learning that further offloads oper...
Federated Learning (FL) has emerged as a promising distributed learning paradigm with an added advan...
Standard centralized machine learning applications require the participants to uploadtheir personal ...
Machine learning models benefit from large and diverse training datasets. However, it is difficult f...
One of the new trends in the field of artificial intelligence is federated learning (FL), which will...
Driven by privacy concerns and the visions of deep learning, the last four years have witnessed a pa...
Federated learning (FL) aims to address the challenges of data silos and privacy protection in artif...
Federated learning is a machine learning technique proposed by Google AI in 2016, as a solution to t...
Federated Learning has witnessed an increasing popularity in the past few years for its ability to t...
The advance of Machine Learning (ML) techniques has become the driving force in the development of A...
The advent of machine learning techniques has given rise to modern devices with built-in models for ...
To preserve participants' privacy, Federated Learning (FL) has been proposed to let participants col...
Federated Learning starts to give a new perspective regarding the applicability of machine learning ...
Federated learning (FL) is a new paradigm that allows several parties to train a model together with...
A possible approach to address the increasing security and privacy concerns is federated learning (F...
Federated learning is an improved version of distributed machine learning that further offloads oper...
Federated Learning (FL) has emerged as a promising distributed learning paradigm with an added advan...
Standard centralized machine learning applications require the participants to uploadtheir personal ...
Machine learning models benefit from large and diverse training datasets. However, it is difficult f...
One of the new trends in the field of artificial intelligence is federated learning (FL), which will...
Driven by privacy concerns and the visions of deep learning, the last four years have witnessed a pa...
Federated learning (FL) aims to address the challenges of data silos and privacy protection in artif...
Federated learning is a machine learning technique proposed by Google AI in 2016, as a solution to t...
Federated Learning has witnessed an increasing popularity in the past few years for its ability to t...
The advance of Machine Learning (ML) techniques has become the driving force in the development of A...
The advent of machine learning techniques has given rise to modern devices with built-in models for ...
To preserve participants' privacy, Federated Learning (FL) has been proposed to let participants col...