Huanhuan Li

TL;DR: This paper combines a distributed many-objective evolutionary algorithm called D-NSGA3 with a greedy algorithm to search the task allocation solutions, and comprehensively considers the constraints related to space, time, energy consumption and agent function in multi-agent systems.

TL;DR: A new NDB generation algorithm that employs a new set of parameters to control the selection of different bits when generating NDB records, and this enables a fine-grained control of the accuracy of distance estimation, and proposes an approach specialized for estimating Euclidean distance from the NDBs generated by the Q K -hidden algorithm.

TL;DR: This paper proposes a method called NStoPS-MLE, which is based on the maximum likelihood estimation, for reconstructing useful information from the collected data and shows that this method can get more accurate aggregated results than previous methods.

TL;DR: This paper proposes a new NDB generation algorithm (named QK-hidden algorithm), and based on this algorithm, a privacy-preserving k-means algorithm which can control the accuracy of distance estimation in a fine-grained manner and thus it can Control the clustering results granularly.

TL;DR: Zhang et al. as mentioned in this paper investigated the security of existing PPDL methods and established a new attack model, which may be exploited by the competitors of the owners of private data, and the experimental results on three public datasets, i.e., MNIST, CIFAR10 and LFW, demonstrate that the selected methods tend to be vulnerable to CAM.