Search Results for author: Leandro L. Minku

Found 8 papers, 3 papers with code

SMOClust: Synthetic Minority Oversampling based on Stream Clustering for Evolving Data Streams

1 code implementation28 Aug 2023 Chun Wai Chiu, Leandro L. Minku

Based on the compressed information, synthetic examples can be created within the region that recently generated new minority class examples.

Clustering imbalanced classification +1

Knowledge Transfer for Dynamic Multi-objective Optimization with a Changing Number of Objectives

no code implementations19 Jun 2023 Gan Ruan, Leandro L. Minku, Stefan Menzel, Bernhard Sendhoff, Xin Yao

Different from most other dynamic multi-objective optimization problems (DMOPs), DMOPs with a changing number of objectives usually result in expansion or contraction of the Pareto front or Pareto set manifold.

Transfer Learning

Evolutionary Optimization for Proactive and Dynamic Computing Resource Allocation in Open Radio Access Network

no code implementations12 Jan 2022 Gan Ruan, Leandro L. Minku, Zhao Xu, Xin Yao

However, the existing problem formulation to solve this resource allocation problem is unsuitable as it defines the capacity utility of resource in an inappropriate way and tends to cause much delay.

A Novel Generalised Meta-Heuristic Framework for Dynamic Capacitated Arc Routing Problems

1 code implementation14 Apr 2021 Hao Tong, Leandro L. Minku, Stefan Menzel, Bernhard Sendhoff, Xin Yao

The few existing studies are limited by the dynamic scenarios considered, and by overly complicated algorithms that are unable to benefit from the wealth of contributions provided by the existing CARP literature.

Metaheuristics "In the Large"

no code implementations19 Nov 2020 Jerry Swan, Steven Adriaensen, Alexander E. I. Brownlee, Kevin Hammond, Colin G. Johnson, Ahmed Kheiri, Faustyna Krawiec, J. J. Merelo, Leandro L. Minku, Ender Özcan, Gisele L. Pappa, Pablo García-Sánchez, Kenneth Sörensen, Stefan Voß, Markus Wagner, David R. White

We describe our vision and report on progress, showing how the adoption of common protocols for all metaheuristics can help liberate the potential of the field, easing the exploration of the design space of metaheuristics.

Multi-Source Transfer Learning for Non-Stationary Environments

1 code implementation7 Jan 2019 Honghui Du, Leandro L. Minku, Huiyu Zhou

To speed up recovery from concept drift and improve predictive performance in data stream mining, this work proposes a novel approach called Multi-sourcE onLine TrAnsfer learning for Non-statIonary Environments (Melanie).

Transfer Learning

Proceedings of the IJCAI 2017 Workshop on Learning in the Presence of Class Imbalance and Concept Drift (LPCICD'17)

no code implementations28 Jul 2017 Shuo Wang, Leandro L. Minku, Nitesh Chawla, Xin Yao

It provides a forum for international researchers and practitioners to share and discuss their original work on addressing new challenges and research issues in class imbalance learning, concept drift, and the combined issues of class imbalance and concept drift.

A Systematic Study of Online Class Imbalance Learning with Concept Drift

no code implementations20 Mar 2017 Shuo Wang, Leandro L. Minku, Xin Yao

As an emerging research topic, online class imbalance learning often combines the challenges of both class imbalance and concept drift.

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