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EvoApps-EML 2020 : EvoApps Special Session on Evolutionary Machine Learning


When Apr 15, 2020 - Apr 17, 2020
Where Seville, Spain
Submission Deadline Nov 15, 2019
Categories    computer science   machine learning   artificial intelligence   evolutionary computation

Call For Papers

The Special Session on Evolutionary Machine Learning (EML) of Evo Apps will provide a specialized forum of discussion and exchange of information for researchers interested in exploring approaches that combine nature and nurture, with the long-term goal of evolving Artificial Intelligence (AI).

Giving response to the growing interest in the area, and consequent advances of the state-of-the-art, the special session covers theoretical and practical advances on the combination of Evolutionary Computation (EC) and Machine Learning (ML) techniques.

Topics of interest include, but are not limited to:
- EC as an ML technique: Using EC to solve typical ML tasks such as Classification or Clustering
- EC applied ML algorithms: Neuroevolution, Feature Selection, Feature Engineering, Evolutionary Adversarial Models
- ML applied to EC: Surrogate-model design by ML for EC, Learning Problem Structure, ML for Diversity, Designing Search Strategies, Predicting Promising Regions, Using ML to Decrease Computational Effort
- Real world applications issues: EC for Fairness, Robustness, Trustworthiness and Explainability; Green EML
- Emerging topics: EC for AutoML; EC for Transfer Learning; EC for Multitasking; Evolving Learning Functions, Neurons and Linkage; EC for Verification and Validation of ML

Important Dates
Extended! Submission deadline: 15 November 2019
Evo*: 15-17 April 2020

Submission details:
Submissions must be original and not published elsewhere. They will be peer reviewed by members of the program committee. The reviewing process will be double-blind, so please omit information about the authors in the submitted paper. Submit your manuscript in Springer LNCS format and provide up to five keywords in your Abstract.

Page limit: 16 pages

Submission link:


Penousal Machado
Wolfgang Banzhaf

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