102 citations · 373 across the 10 of their papers we have counts for
11 papers
Mitigating Unfairness via Evolutionary Multi-objective Ensemble Learning
Qingquan Zhang, Jialin Liu, Zeqi Zhang +3
In the literature of mitigating unfairness in machine learning, many fairness measures are designed to evaluate predictions of learning models and also utilised to guide the traini…
A Novel CNet-assisted Evolutionary Level Repairer and Its Applications to Super Mario Bros
Tianye Shu, Ziqi Wang, Jialin Liu +1
Applying latent variable evolution to game level design has become more and more popular as little human expert knowledge is required. However, defective levels with illegal patter…
How to Evaluate Solutions in Pareto-based Search-Based Software Engineering? A Critical Review and Methodological Guidance
Miqing Li, Tao Chen, Xin Yao
With modern requirements, there is an increasing tendency of considering multiple objectives/criteria simultaneously in many Software Engineering (SE) scenarios. Such a multi-objec…
Synergizing Domain Expertise with Self-Awareness in Software Systems: A Patternized Architecture Guideline
Tao Chen, Rami Bahsoon, Xin Yao
To promote engineering self-aware and self-adaptive software systems in a reusable manner, architectural patterns and the related methodology provide an unified solution to handle…
Adaptive Initialization Method for K-means Algorithm
Jie Yang, Yu-Kai Wang, Xin Yao +1
The K-means algorithm is a widely used clustering algorithm that offers simplicity and efficiency. However, the traditional K-means algorithm uses the random method to determine th…
A Simple Yet Effective Approach to Robust Optimization Over Time
Lukáš Adam, Xin Yao
Robust optimization over time (ROOT) refers to an optimization problem where its performance is evaluated over a period of future time. Most of the existing algorithms use particle…
Learning Topological Representation for Networks via Hierarchical Sampling
Guoji Fu, Chengbin Hou, Xin Yao
The topological information is essential for studying the relationship between nodes in a network. Recently, Network Representation Learning (NRL), which projects a network into a…
Representation Learning for Heterogeneous Information Networks via Embedding Events
Guoji Fu, Bo Yuan, Qiqi Duan +1
Network representation learning (NRL) has been widely used to help analyze large-scale networks through mapping original networks into a low-dimensional vector space. However, exis…
Evolutionary Generative Adversarial Networks
Chaoyue Wang, Chang Xu, Xin Yao +1
Generative adversarial networks (GAN) have been effective for learning generative models for real-world data. However, existing GANs (GAN and its variants) tend to suffer from trai…
A Survey and Taxonomy of Self-Aware and Self-Adaptive Cloud Autoscaling Systems
Tao Chen, Rami Bahsoon, Xin Yao
Autoscaling system can reconfigure cloud-based services and applications, through various configurations of cloud software and provisions of hardware resources, to adapt to the cha…
FEMOSAA: Feature Guided and Knee Driven Multi-Objective Optimization for Self-Adaptive Software
Tao Chen, Ke Li, Rami Bahsoon +1
Self-adaptive software (SAS) can reconfigure itself to adapt to the changing environment at runtime, aiming for continually optimizing conflicted non-functional objectives, e.g., r…