Alexey Zabashta

Orcid: 0000-0002-7494-4309

According to our database1, Alexey Zabashta authored at least 9 papers between 2015 and 2021.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2021
Improving Multimodal Data Labeling with Deep Active Learning for Post Classification in Social Networks.
Proceedings of the MULL'21: Multimedia Understanding with Less Labeling on Multimedia Understanding with Less Labeling, 2021

2020
Stabilization of Dataset Matrix Form for Classification Dataset Generation and Algorithm Selection.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2020, 2020

Graph Convolutional Network Based Generative Adversarial Networks for the Algorithm Selection Problem in Classification.
Proceedings of the CCRIS 2020: International Conference on Control, 2020

2019
Active Dataset Generation for Meta-learning System Quality Improvement.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2019, 2019

Generating Datasets for Classification Task and Predicting Best Classifiers with Conditional Generative Adversarial Networks.
Proceedings of the 3rd International Conference on Advances in Artificial Intelligence, 2019

Synthesis of Datasets with Specific Characteristics for the Clustering Problem.
Proceedings of the CSAI 2019: 2019 3rd International Conference on Computer Science and Artificial Intelligence, 2019

2017
NDSE: Instance Generation for Classification by Given Meta-Feature Description.
Proceedings of the International Workshop on Automatic Selection, 2017

2016
Rank Aggregation Algorithm Selection Meets Feature Selection.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2016

2015
Study on Meta-Learning Approach Application in Rank Aggregation Algorithm Selection.
Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2015 (ECMLPKDD 2015), 2015


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