b'Yaochu Jin'

research

∙ 03/07/2023

Evolutionary Reinforcement Learning: A Survey

Reinforcement learning (RL) is a machine learning approach that trains a...

0 Hui Bai, et al. ∙

research

∙ 02/28/2023

Augmented Transformers with Adaptive n-grams Embedding for Multilingual Scene Text Recognition

While vision transformers have been highly successful in improving the p...

0 Xueming Yan, et al. ∙

research

∙ 01/31/2023

IM-IAD: Industrial Image Anomaly Detection Benchmark in Manufacturing

Image anomaly detection (IAD) is an emerging and vital computer vision t...

0 Guoyang Xie, et al. ∙

research

∙ 01/29/2023

EvoX: A Distributed GPU-accelerated Library towards Scalable Evolutionary Computation

During the past decades, evolutionary computation (EC) has demonstrated ...

0 Beichen Huang, et al. ∙

research

∙ 01/28/2023

Pushing the Limits of Fewshot Anomaly Detection in Industry Vision: Graphcore

In the area of fewshot anomaly detection (FSAD), efficient visual featur...

0 Guoyang Xie, et al. ∙

research

∙ 01/27/2023

Deep Industrial Image Anomaly Detection: A Survey

The recent rapid development of deep learning has laid a milestone in in...

0 Jiaqi Liu, et al. ∙

research

∙ 01/26/2023

A Graph Neural Network with Negative Message Passing for Graph Coloring

Graph neural networks have received increased attention over the past ye...

0 Xiangyu Wang, et al. ∙

research

∙ 11/21/2022

Intelligent Computing: The Latest Advances, Challenges and Future

Computing is a critical driving force in the development of human civili...

16 Shiqiang Zhu, et al. ∙

research

∙ 10/27/2022

End-to-End Pareto Set Prediction with Graph Neural Networks for Multi-objective Facility Location

The facility location problems (FLPs) are a typical class of NP-hard com...

0 Shiqing Liu, et al. ∙

research

∙ 10/15/2022

A Secure Federated Data-Driven Evolutionary Multi-objective Optimization Algorithm

Data-driven evolutionary algorithms usually aim to exploit the informati...

0 Qiqi Liu, et al. ∙

research

∙ 09/20/2022

Rethinking Individual Global Max in Cooperative Multi-Agent Reinforcement Learning

In cooperative multi-agent reinforcement learning, centralized training ...

0 Yitian Hong, et al. ∙

research

∙ 08/25/2022

Alleviating Search Bias in Bayesian Evolutionary Optimization with Many Heterogeneous Objectives

Multi-objective optimization problems whose objectives have different ev...

0 Xilu Wang, et al. ∙

research

∙ 08/23/2022

Survey on Evolutionary Deep Learning: Principles, Algorithms, Applications and Open Issues

Over recent years, there has been a rapid development of deep learning (...

0 Nan Li, et al. ∙

research

∙ 08/08/2022

Neural Architecture Search as Multiobjective Optimization Benchmarks: Problem Formulation and Performance Assessment

The ongoing advancements in network architecture design have led to rema...

0 Zhichao Lu, et al. ∙

research

∙ 07/22/2022

Towards Fairness-Aware Multi-Objective Optimization

Recent years have seen the rapid development of fairness-aware machine l...

0 Guo Yu, et al. ∙

research

∙ 07/12/2022

Bi-fidelity Evolutionary Multiobjective Search for Adversarially Robust Deep Neural Architectures

Deep neural networks have been found vulnerable to adversarial attacks, ...

0 Jia Liu, et al. ∙

research

∙ 06/07/2022

Recent Advances in Bayesian Optimization

Bayesian optimization has emerged at the forefront of expensive black-bo...

0 Xilu Wang, et al. ∙

research

∙ 06/03/2022

A Survey on Surrogate-assisted Efficient Neural Architecture Search

Neural architecture search (NAS) has become increasingly popular in the ...

0 Shiqing Liu, et al. ∙

research

∙ 02/14/2022

A Survey of Visual Sensory Anomaly Detection

Visual sensory anomaly detection (AD) is an essential problem in compute...

0 Xi Jiang, et al. ∙

research

∙ 02/14/2022

A Survey of Cross-Modality Brain Image Synthesis

The existence of completely aligned and paired multi-modal neuroimaging ...

0 Guoyang Xie, et al. ∙

research

∙ 02/14/2022

A Generic Self-Supervised Framework of Learning Invariant Discriminative Features

Self-supervised learning (SSL) has become a popular method for generatin...

0 Foivos Ntelemis, et al. ∙

research

∙ 01/29/2022

FedMed-ATL: Misaligned Unpaired Brain Image Synthesis via Affine Transform Loss

The existence of completely aligned and paired multi-modal neuroimaging ...

0 Guoyang Xie, et al. ∙

research

∙ 01/22/2022

FedMed-GAN: Federated Multi-Modal Unsupervised Brain Image Synthesis

Utilizing the paired multi-modal neuroimaging data has been proved to be...

0 Guoyang Xie, et al. ∙

research

∙ 08/30/2021

Transfer Learning Based Co-surrogate Assisted Evolutionary Bi-objective Optimization for Objectives with Non-uniform Evaluation Times

Most existing multiobjetive evolutionary algorithms (MOEAs) implicitly a...

2 Xilu Wang, et al. ∙

research

∙ 06/22/2021

A Federated Data-Driven Evolutionary Algorithm for Expensive Multi/Many-objective Optimization

Data-driven optimization has found many successful applications in the r...

0 Jinjin Xu, et al. ∙

research

∙ 06/12/2021

Federated Learning on Non-IID Data: A Survey

Federated learning is an emerging distributed machine learning framework...

0 Hangyu Zhu, et al. ∙

research

∙ 05/22/2021

Principled Design of Translation, Scale, and Rotation Invariant Variation Operators for Metaheuristics

In the past three decades, a large number of metaheuristics have been pr...

10 Ye Tian, et al. ∙

research

∙ 03/12/2021

Information Maximization Clustering via Multi-View Self-Labelling

Image clustering is a particularly challenging computer vision task, whi...

0 Foivos Ntelemis, et al. ∙

research

∙ 02/28/2021

Tiny Adversarial Mulit-Objective Oneshot Neural Architecture Search

Due to limited computational cost and energy consumption, most neural ne...

0 Guoyang Xie, et al. ∙

research

∙ 02/16/2021

A Federated Data-Driven Evolutionary Algorithm

Data-driven evolutionary optimization has witnessed great success in sol...

0 Jinjin Xu, et al. ∙

research

∙ 01/16/2021

Multi-objective Search of Robust Neural Architectures against Multiple Types of Adversarial Attacks

Many existing deep learning models are vulnerable to adversarial example...

10 Jia Liu, et al. ∙

research

∙ 01/10/2021

Adaptive Prototypical Networks with Label Words and Joint Representation Learning for Few-Shot Relation Classification

Relation classification (RC) task is one of fundamental tasks of informa...

8 Yan Xiao, et al. ∙

research

∙ 12/14/2020

Incremental Data-driven Optimization of Complex Systems in Nonstationary Environments

Existing work on data-driven optimization focuses on problems in static ...

0 Cuie Yang, et al. ∙

research

∙ 11/25/2020

Distributed Additive Encryption and Quantization for Privacy Preserving Federated Deep Learning

Homomorphic encryption is a very useful gradient protection technique us...

0 Hangyu Zhu, et al. ∙

research

∙ 11/08/2020

Image Clustering using an Augmented Generative Adversarial Network and Information Maximization

Image clustering has recently attracted significant attention due to the...

26 Foivos Ntelemis, et al. ∙

research

∙ 09/12/2020

From Federated Learning to Federated Neural Architecture Search: A Survey

Federated learning is a recently proposed distributed machine learning p...

0 Hangyu Zhu, et al. ∙

research

∙ 03/27/2020

Generation of Consistent Sets of Multi-Label Classification Rules with a Multi-Objective Evolutionary Algorithm

Multi-label classification consists in classifying an instance into two ...

0 Thiago Zafalon Miranda, et al. ∙

research

∙ 03/07/2020

Sampled Training and Node Inheritance for Fast Evolutionary Neural Architecture Search

The performance of a deep neural network is heavily dependent on its arc...

0 Haoyu Zhang, et al. ∙

research

∙ 03/07/2020

Ternary Compression for Communication-Efficient Federated Learning

Learning over massive data stored in different locations is essential in...

0 Jinjin Xu, et al. ∙

research

∙ 03/04/2020

Real-time Federated Evolutionary Neural Architecture Search

Federated learning is a distributed machine learning approach to privacy...

0 Hangyu Zhu, et al. ∙

research

∙ 12/23/2019

A Survey of Deep Learning Applications to Autonomous Vehicle Control

Designing a controller for autonomous vehicles capable of providing adeq...

41 Sampo Kuutti, et al. ∙

research

∙ 11/14/2019

CMSN: Continuous Multi-stage Network and Variable Margin Cosine Loss for Temporal Action Proposal Generation

Accurately locating the start and end time of an action in untrimmed vid...

8 Yushuai Hu, et al. ∙

research

∙ 10/20/2019

Identification of Interaction Clusters Using a Semi-supervised Hierarchical Clustering Method

Motivation: Identifying interaction clusters of large gene regulatory ne...

0 Yu Chen, et al. ∙

research

∙ 10/11/2019

Evolutionary Multi-Objective Optimization Driven by Generative Adversarial Networks (GANs)

Recently, more and more works have proposed to drive evolutionary algori...

20 Cheng He, et al. ∙

research

∙ 07/10/2019

Evolutionary Multi-Objective Optimization Driven by Generative Adversarial Networks

Recently, more and more works have proposed to drive evolutionary algori...

12 Cheng He, et al. ∙

research

∙ 03/18/2019

Communication-Efficient Federated Deep Learning with Asynchronous Model Update and Temporally Weighted Aggregation

Federated learning obtains a central model on the server by aggregating ...

0 Yang Chen, et al. ∙

research

∙ 12/18/2018

Multi-objective Evolutionary Federated Learning

Federated learning is an emerging technique used to prevent the leakage ...

40 Hangyu Zhu, et al. ∙

research

∙ 08/28/2018

A Particle Filter based Multi-Objective Optimization Algorithm: PFOPS

This letter is concerned with a recently developed paradigm of populatio...

0 Bin Liu, et al. ∙

research

∙ 06/08/2017

Evolutionary Multitasking for Multiobjective Continuous Optimization: Benchmark Problems, Performance Metrics and Baseline Results

In this report, we suggest nine test problems for multi-task multi-objec...

0 Yuan Yuan, et al. ∙

research

∙ 02/20/2017

An Efficient Method for online Detection of Polychronous Patterns in Spiking Neural Network

Polychronous neural groups are effective structures for the recognition ...

0 Joseph Chrol-Cannon, et al. ∙

Yaochu Jin

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