587 citations · 2k across the 58 of their papers we have counts for
9 papers · 1 filter
Incremental Data-driven Optimization of Complex Systems in Nonstationary Environments
Cuie Yang, Jinliang Ding, Yaochu Jin +1
Existing work on data-driven optimization focuses on problems in static environments, but little attention has been paid to problems in dynamic environments. This paper proposes a…
Distributed Additive Encryption and Quantization for Privacy Preserving Federated Deep Learning
Hangyu Zhu, Rui Wang, Yaochu Jin +2
Homomorphic encryption is a very useful gradient protection technique used in privacy preserving federated learning. However, existing encrypted federated learning systems need a t…
Image Clustering using an Augmented Generative Adversarial Network and Information Maximization
Foivos Ntelemis, Yaochu Jin, Spencer A. Thomas
Image clustering has recently attracted significant attention due to the increased availability of unlabelled datasets. The efficiency of traditional clustering algorithms heavily…
From Federated Learning to Federated Neural Architecture Search: A Survey
Hangyu Zhu, Haoyu Zhang, Yaochu Jin
Federated learning is a recently proposed distributed machine learning paradigm for privacy preservation, which has found a wide range of applications where data privacy is of prim…
Generation of Consistent Sets of Multi-Label Classification Rules with a Multi-Objective Evolutionary Algorithm
Thiago Zafalon Miranda, Diorge Brognara Sardinha, Márcio Porto Basgalupp +2
Multi-label classification consists in classifying an instance into two or more classes simultaneously. It is a very challenging task present in many real-world applications, such…
Hybrid Attention-Based Transformer Block Model for Distant Supervision Relation Extraction
Yan Xiao, Yaochu Jin, Ran Cheng +1
With an exponential explosive growth of various digital text information, it is challenging to efficiently obtain specific knowledge from massive unstructured text information. As…
Sampled Training and Node Inheritance for Fast Evolutionary Neural Architecture Search
Haoyu Zhang, Yaochu Jin, Ran Cheng +1
The performance of a deep neural network is heavily dependent on its architecture and various neural architecture search strategies have been developed for automated network archit…
Real-time Federated Evolutionary Neural Architecture Search
Hangyu Zhu, Yaochu Jin
Federated learning is a distributed machine learning approach to privacy preservation and two major technical challenges prevent a wider application of federated learning. One is t…
Ternary Compression for Communication-Efficient Federated Learning
Jinjin Xu, Wenli Du, Ran Cheng +2
Learning over massive data stored in different locations is essential in many real-world applications. However, sharing data is full of challenges due to the increasing demands of…