Run transferable libraries - Learning functional bias in problem domains

被引：0

作者：

Keijzer, M ^{[1
]}

Ryan, C

Cattolico, M

机构：

[1] Prognosys, Utrecht, Netherlands

[2] Univ Limerick, Limerick, Ireland

[3] Tiger Mt Sci Inc, Kirkland, WA USA

来源：

GENETIC AND EVOLUTIONARY COMPUTATION GECCO 2004 , PT 2, PROCEEDINGS | 2004年 / 3103卷

关键词：

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper introduces the notion of Run Transferable Libraries, a mechanism to pass knowledge acquired in one GP run to another. We demonstrate that a system using these libraries can solve a selection of standard benchmarks considerably more quickly than GP with ADFs by building knowledge about a problem. Further, we demonstrate that a GP system with these libraries can scale much better than a standard ADF GP system when trained initially on simpler versions of difficult problems.

引用

页码：531 / 542

页数：12

共 50 条

[41] An intelligent mobile location-aware book recommendation system that enhances problem-based learning in libraries
Chen, Chih-Ming
INTERACTIVE LEARNING ENVIRONMENTS, 2013, 21 (05) : 469 - 495
[42] Problem-based learning supported by digital archives Case study of Taiwan Libraries' History Digital Library
Chen, Chih-Ming
Chen, Chia-Chi
ELECTRONIC LIBRARY, 2010, 28 (01): : 5 - 28
[43] Integrating Bayesian Calibration, Bias Correction, and Machine Learning for the 2014 Sandia Verification and Validation Challenge Problem
Li W.
Chen S.
Jiang Z.
Apley D.W.
Lu Z.
Chen W.
Journal of Verification, Validation and Uncertainty Quantification, 2016, 1 (01):
[44] Identifying longitudinal growth trajectories of learning domains in problem-based learning: a latent growth curve modeling approach using SEM
Paul F. Wimmers
Ming Lee
Advances in Health Sciences Education, 2015, 20 : 467 - 478
[45] Identifying longitudinal growth trajectories of learning domains in problem-based learning: a latent growth curve modeling approach using SEM
Wimmers, Paul F.
Lee, Ming
ADVANCES IN HEALTH SCIENCES EDUCATION, 2015, 20 (02) : 467 - 478
[46] A MULTIMODAL LEARNING FRAMEWORK TO STUDY VARYING INFORMATION COMPLEXITY IN STRUCTURAL AND FUNCTIONAL SUB-DOMAINS IN SCHIZOPHRENIA
Batta, Ishaan
Abrol, Anees
Fu, Zening
Calhoun, Vince
2021 IEEE 18TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI), 2021, : 994 - 998
[47] Transfer Between Reading Comprehension and Word-Problem Solving Among Children With Learning Difficulty in Both Domains
Fuchs, Lynn S.
Seethaler, Pamela M.
Sterba, Sonya K.
Fuchs, Douglas
Cutting, Laurie E.
Mancilla-Martinez, Jeannette
Martin, BrittanyLee N.
Espinas, Daniel
JOURNAL OF EDUCATIONAL PSYCHOLOGY, 2024, 116 (07) : 1093 - 1111
[48] Age-stratified distress thermometers with Worry and Learning problem domains for the paediatric oncology population: Development and validation
Cuffe, Ray
Norman, Catherine
Haeems, Gabriella
Spicer, Lucy
Mohammed, Kabir
Rodger, Melanie
Edwards, Lesley
PSYCHO-ONCOLOGY, 2022, 31 (05) : 832 - 839
[49] Design of a Dual-Mapping Learning Approach for Problem Solving and Knowledge Construction in Ill-Structured Domains
Wu, Bian
Wang, Minhong
Spector, J. Michael
Yang, Stephen J. H.
EDUCATIONAL TECHNOLOGY & SOCIETY, 2013, 16 (04): : 71 - 84
[50] DO DEEP LEARNING MODELS GENERALIZE TO OVERHEAD IMAGERY FROM NOVEL GEOGRAPHIC DOMAINS? THE XGD BENCHMARK PROBLEM
Huang, Bohao
Bradbury, Kyle
Collins, Leslie M.
Malof, Jordan M.
IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2020, : 1476 - 1479

← 1 2 3 4 5 →