Interactive Evolutionary Multiobjective Optimization via Learning to Rank-Reference-Cited by-同舟云学术

Interactive Evolutionary Multiobjective Optimization via Learning to Rank

Published:2023-08 Issue:4 Volume:27 Page:749-763
ISSN:1089-778X
Container-title:IEEE Transactions on Evolutionary Computation
language:
Short-container-title:IEEE Trans. Evol. Computat.

Author:

Li Ke¹^ORCID,Lai Guiyu¹,Yao Xin²^ORCID

Affiliation:

1. College of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China

2. Department of Computer Science and Engineering, Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation, Southern University of Science and Technology, Shenzhen, China

Funder

UKRI Future Leaders Fellowship

NSFC

Royal Society

EPSRC

Amazon Research Award

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Theoretical Computer Science,Software

Link

http://xplorestaging.ieee.org/ielx7/4235/10198499/10015671.pdf?arnumber=10015671

Reference72 articles.

1. Learning to Rank for Information Retrieval

2. R2-Based Hypervolume Contribution Approximation

3. An Interactive Simple Indicator-Based Evolutionary Algorithm (I-SIBEA) for Multiobjective Optimization Problems

4. Evaluating the quality of approximations of the non-dominated set;hansen,1987

5. Learning Preference Models in Recommender Systems

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