
Adaptive Initialization Method for Kmeans Algorithm
The Kmeans algorithm is a widely used clustering algorithm that offers ...
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Learning Topological Representation for Networks via Hierarchical Sampling
The topological information is essential for studying the relationship b...
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Does Preference Always Help? A Holistic Study on PreferenceBased Evolutionary MultiObjective Optimisation Using Reference Points
The ultimate goal of multiobjective optimisation is to help a decision ...
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Synergizing Domain Expertise with SelfAwareness in Software Systems: A Patternized Architecture Guideline
Architectural patterns provide a reusable architectural solution for com...
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Algorithm Portfolio for Individualbased SurrogateAssisted Evolutionary Algorithms
Surrogateassisted evolutionary algorithms (SAEAs) are powerful optimisa...
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A Novel CNetassisted Evolutionary Level Repairer and Its Applications to Super Mario Bros
Applying latent variable evolution to game level design has become more ...
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What Weights Work for You? Adapting Weights for Any Pareto Front Shape in Decompositionbased Evolutionary MultiObjective Optimisation
The quality of solution sets generated by decompositionbased evolutiona...
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Evolutionary Multitasking for Singleobjective Continuous Optimization: Benchmark Problems, Performance Metric, and Baseline Results
In this report, we suggest nine test problems for multitask singleobje...
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How to Read ManyObjective Solution Sets in Parallel Coordinates
Rapid development of evolutionary algorithms in handling manyobjective ...
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Experiencebased Optimization: A Coevolutionary Approach
This paper studies improving solvers based on their past solving experie...
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Dominance Move: A Measure of Comparing Solution Sets in Multiobjective Optimization
One of the most common approaches for multiobjective optimization is to ...
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Integration of Preferences in Decomposition MultiObjective Optimization
Most existing studies on evolutionary multiobjective optimization focus...
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Dynamic MultiObjectives Optimization with a Changing Number of Objectives
Existing studies on dynamic multiobjective optimization focus on proble...
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A Unified Markov Chain Approach to Analysing Randomised Search Heuristics
The convergence, convergence rate and expected hitting time play fundame...
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Average Drift Analysis and Population Scalability
This paper aims to study how the population size affects the computation...
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Convex HullBased Multiobjective Genetic Programming for Maximizing ROC Performance
ROC is usually used to analyze the performance of classifiers in data mi...
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A Large Population Size Can Be Unhelpful in Evolutionary Algorithms
The utilization of populations is one of the most important features of ...
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On the Easiest and Hardest Fitness Functions
The hardness of fitness functions is an important research topic in the ...
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Kernel Truncated Regression Representation for Robust Subspace Clustering
Subspace clustering aims to group data points into multiple clusters of ...
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On the Impact of MutationSelection Balance on the Runtime of Evolutionary Algorithms
The interplay between mutation and selection plays a fundamental role in...
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On the approximation ability of evolutionary optimization with application to minimum set cover
Evolutionary algorithms (EAs) are heuristic algorithms inspired by natur...
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Highdimensional Blackbox Optimization via Divide and Approximate Conquer
Divide and Conquer (DC) is conceptually well suited to highdimensional ...
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Probabilistic Feature Selection and Classification Vector Machine
Sparse Bayesian learning is one of the stateof theart machine learnin...
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Negatively Correlated Search
Evolutionary Algorithms (EAs) have been shown to be powerful tools for c...
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Learning in the Model Space for Fault Diagnosis
The emergence of large scaled sensor networks facilitates the collection...
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Scaling Up Estimation of Distribution Algorithms For Continuous Optimization
Since Estimation of Distribution Algorithms (EDA) were proposed, many at...
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The Impact of Mutation Rate on the Computation Time of Evolutionary Dynamic Optimization
Mutation has traditionally been regarded as an important operator in evo...
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Evolutionary Mechanics: new engineering principles for the emergence of flexibility in a dynamic and uncertain world
Engineered systems are designed to deftly operate under predetermined co...
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TwoArchive Evolutionary Algorithm for Constrained MultiObjective Optimization
When solving constrained multiobjective optimization problems, an impor...
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Interactive Decomposition MultiObjective Optimization via Progressively Learned Value Functions
Decomposition has become an increasingly popular technique for evolution...
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Automatic Construction of Parallel Portfolios via Explicit Instance Grouping
Simultaneously utilizing several complementary solvers is a simple yet e...
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Maximizing Nonmonotone/Nonsubmodular Functions by Multiobjective Evolutionary Algorithms
Evolutionary algorithms (EAs) are a kind of natureinspired generalpurp...
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Evolutionary Generative Adversarial Networks
Generative adversarial networks (GAN) have been effective for learning g...
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Multiobjective Test Problems with Degenerate Pareto Fronts
In multiobjective optimization, a set of scalable test problems with a v...
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Analysis of Noisy Evolutionary Optimization When Sampling Fails
In noisy evolutionary optimization, sampling is a common strategy to dea...
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Representation Learning for Heterogeneous Information Networks via Embedding Events
Network representation learning (NRL) has been widely used to help analy...
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Tiyuntsong: A SelfPlay Reinforcement Learning Approach for ABR Video Streaming
Existing reinforcement learning(RL)based adaptive bitrate(ABR) approach...
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A Parallel DivideandConquer based Evolutionary Algorithm for Largescale Optimization
Largescale optimization problems that involve thousands of decision var...
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Voronoibased Efficient Surrogateassisted Evolutionary Algorithm for Very Expensive Problems
Very expensive problems are very common in practical system that one fit...
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A Simple Yet Effective Approach to Robust Optimization Over Time
Robust optimization over time (ROOT) refers to an optimization problem w...
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Federated Learning with Additional Mechanisms on Clients to Reduce Communication Costs
Federated learning (FL) enables ondevice training over distributed netw...
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Competitive Coevolution for Dynamic Constrained Optimisation
Dynamic constrained optimisation problems (DCOPs) widely exist in the re...
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Federated Learning with Unbiased Gradient Aggregation and Controllable Meta Updating
Federated Averaging (FedAvg) serves as the fundamental framework in Fede...
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Adversarial Feature Alignment: Avoid Catastrophic Forgetting in Incremental Task Lifelong Learning
Human beings are able to master a variety of knowledge and skills with o...
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On Performance Estimation in Automatic Algorithm Configuration
Over the last decade, research on automated parameter tuning, often refe...
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Comyco: QualityAware Adaptive Video Streaming via Imitation Learning
Learningbased Adaptive Bit Rate (ABR) method, aiming to learn outstandi...
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Negatively Correlated Search as a Parallel Exploration Search Strategy
Parallel exploration is a key to a successful search. The recently propo...
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How to Evaluate Solutions in Paretobased SearchBased Software Engineering? A Critical Review and Methodological Guidance
With modern requirements, there is an increasing tendancy of considering...
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Dynamic Multiobjective Optimization of the Travelling Thief Problem
Investigation of detailed and complex optimisation problem formulations ...
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Analysis of Evolutionary Algorithms on Fitness Function with Timelinkage Property
In realworld applications, many optimization problems have the timelin...
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Xin Yao
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Professor of Computer Science in the School of Computer Science at the University of Birmingham and the Director of the Centre of Excellence for Research in Computational Intelligence and Applications (CERCIA)