Author

Katerina Potika

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Preprint Aug 2026

Concept Drift Detection and Adaptive Retraining of Malware Classification Models

Concept drift refers to changes over time in the statistical properties of data, as compared to the data that was used to train a learning model. Machine learning models for malware detection or classification are particularly susceptible to performance degradation caused by concept drift, as attackers constantly modif...

C. Chungata, Martin Jurecek, Katerina Potika et al. · 0 citations

#graph neural networks Preprint Aug 2026

GATNextHop: A GAT for Shortest Path Routing with Cross-Topology Generalization

The GATNextHop model is proposed to determine whether a Graph Neural Network, namely the Graph Attention Network, can approximate shortest paths and generalize across topologies and compares the GNN against Dijkstra's algorithm to quantify trade-offs between learned and classical routing approaches.

Chia-Hong Chou, Katerina Potika · 0 citations

Conference Jul 2026

Fair Influence Maximization with Reverse Influence Sampling Boosted Multi-Objective Genetic Algorithm

Influence maximization (IM) selects a small set of seed users to maximize expected diffusion in a social network, typically under the Independent Cascade model. Optimizing only global spread can amplify pre-existing structural inequities: some groups (e.g., demographics, communities, or departments) may receive far les...

Akash Janardhan Srinivas, Petros Potikas, William B. Andreopoulos et al. · International Conference on... · 0 citations