Pitfalls in Instance Generation for Udine Timetabling

2010 ◽  
pp. 299-302 ◽  
Author(s):  
Leo Lopes ◽  
Kate Smith-Miles
Keyword(s):  
Instance Generation

Adversarial Imbalance Classification with Class-Specific Diverse Instance Generation

2021 ◽  
Author(s):  
Qihang Shen ◽  
Xinyue Wang ◽  
Zixin Cai ◽  
Liping Jing
Keyword(s):  
Instance Generation

scholarly journals Hard instance generation for SAT

1997 ◽  
pp. 22-31 ◽  
Author(s):  
Satoshi Horie ◽  
Osamu Watanabe
Keyword(s):  
Instance Generation

An SMT-based Approach for Generating Coverage Oriented Metamodel Instances

2016 ◽  
Vol 7 (3) ◽  
pp. 23-50 ◽  
Author(s):  
Hao Wu
Keyword(s):  
General Level ◽  
Effective Technique ◽  
Coverage Criteria ◽  
Smt Solver ◽  
Instance Generation ◽  
Graph Property ◽  
Class Diagrams

An effective technique for generating instances of a metamodel should quickly and automatically generate instances satisfying the metamodel's structural and OCL constraints. Ideally it should also produce quantitatively meaningful instances with respect to certain criteria, that is, instances which meet specified generic coverage criteria that help the modelers test or verify a metamodel at a general level. In this paper, the author presents an approach consisting of two techniques for coverage oriented metamodel instance generation. The first technique realises the standard coverage criteria defined for UML class diagrams, while the second technique focuses on generating instances satisfying graph-based criteria. With the author's approach, both kinds of criteria are translated to SMT formulas which are then investigated by an SMT solver. Each successful assignment is then interpreted as a metamodel instance that provably satisfies a coverage criteria or a graph property. The author has already integrated this approach into his existing tool to demonstrate the feasibility.

MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation

2015 ◽  
Vol 89 ◽  
pp. 385-397 ◽  
Author(s):  
Francisco Charte ◽  
Antonio J. Rivera ◽  
María J. del Jesus ◽  
Francisco Herrera
Keyword(s):  
Multilabel Learning ◽  
Instance Generation

Instance Generation

1997 ◽  
pp. 69-94
Author(s):  
Alf Kimms
Keyword(s):  
Instance Generation
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