Call for Papers - Special Session on Active Learning for Concept and Feature Drift Detection

2022 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAISS)

May 25-27 2022, Larnaca, Cyprus (http://cyprusconferences.org/eais2022/)

Important Dates

Paper submission: January 10, 2022

Notification of acceptance: February 19, 2022

Aims and Scope

In the Deep Learning (DL) hyperconnected era, classifiers consume labels and labelled data at unprecedented rates. While computational power is no more an issue in model training, the time, cost, or human supervision required to produce high quality labelled data seriously hinders the maximum size of the available labelled datasets and hence the extensibility of DL in many challenging domains. To tackle the label-scarcity problem, Transfer Learning (TL) and Active Learning (AL) have both been exploited, the former using pre-trained models from a different domain and the latter choosing the best subset of instances to be labelled. Specifically, in the case of streaming data, labels may not be available for each instance of the stream (or being very costly, or come too fast for a human expert), data may have a very short lifespan, batch methods are unenforceable and issues due to concept and feature drift, or model switch, may prevent the training to be effective. The aim of the special session is to host original papers and reviews on recent research advances and state‐of‐the‐art methods in the fields of Computational Intelligence, Machine Learning, Data Mining and Distributed Computing methodologies concerning TL and AL techniques for concept and feature drift detection on streaming data.

Relevant topics within this context include, but are not limited to:

Computational Intelligence

Machine learning and Deep Learning

Sparse Coding

Data Mining

Fuzzy and Neuro‐Fuzzy Systems

Probabilistic and statistical modelling

Active Learning

Transfer Learning

Cost-Sensitive Learning

Online Learning

Concept Drift Detection

Feature Drift Detection

Online Feature Learning/Extraction/Selection

Submission

- Submissions of full papers are accepted online through EasyChair system

- For paper guidelines please visit http://cyprusconferences.org/eais2022/

Organizers

- Angelo Ciaramella, Università degli Studi di Napoli "Parthenope", Italy

- Alessio Ferone, Università degli Studi di Napoli "Parthenope", Italy

- Giosuè Lo Bosco, Università degli Studi di Palermo, Italy

- Antonio Maratea, Università degli Studi di Napoli "Parthenope", Italy

- Le Hoang Son, Vietnam National University, Hanoi

Contact

Angelo Ciaramella, angelo.ciaramella@uniparthenope.it

Alessio Ferone, alessio.ferone@uniparthenope.it

Antonio Maratea, antonio.maratea@uniparthenope.it