activity
20202026
most citedConvolutional Neural Networks for Image Spam Detection

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

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

Chia-Hong Chou, Katerina Potika

Common shortest-path algorithms, such as Dijkstra's (SPF), that OSPF uses, provide exact routing solutions but must be recomputed for each network topology, limiting scalability in…

cs.LG2026

Concept Drift Detection and Adaptive Retraining of Malware Classification Models

Christofer Washington Berruz Chungata, Martin Jurecek, Katerina Potika +2

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 malwar…

cs.LG2026

GaLoRA: Parameter-Efficient Graph-Aware LLMs for Node Classification

Mayur Choudhary, Saptarshi Sengupta, Katerina Potika

The rapid rise of large language models (LLMs) and their ability to capture semantic relationships has led to their adoption in a wide range of applications. Text-attributed graphs…

cs.CV20222 cited

Convolutional Neural Networks for Image Spam Detection

Tazmina Sharmin, Fabio Di Troia, Katerina Potika +1

Spam can be defined as unsolicited bulk email. In an effort to evade text-based filters, spammers sometimes embed spam text in an image, which is referred to as image spam. In this…

math.CO2020

Improved algorithm to determine 3-colorability of graphs with the minimum degree at least 7

Nicholas Crawford, Sogol Jahanbekam, Katerina Potika

Let be an -vertex graph with the maximum degree and the minimum degree . We give algorithms with complexity and that…