Portfolio item number 1
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Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1).
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Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2).
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Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3).
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Published in European Conference on Artificial Intelligence (ECAI), 2025
This paper presents iHOMER, a novel framework for online multi-label learning in dynamic environments. iHOMER is the first incremental, drift-aware algorithm that partitions the label space into correlated clusters without requiring predefined hierarchies. It adapts to concept drift over time, balances scalability and predictive performance, and employs statistical tests to guide both splitting and merging of label clusters.
Recommended citation: Neves, L., Lourenço, A., Cano, A., & Marreiros, G. (2025). Online hierarchical partitioning of the output space in extreme multi-label data streams. GECAD, ISEP, Polytechnic of Porto; Virginia Tech.
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Published:
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Published:
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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