9 citations · 12 across the 4 of their papers we have counts for
5 papers
Segment-Level Agentic Topic Modeling for Improved Data Exploration and Resource Efficiency
Myeongjun Erik Jang, Antonios Georgiadis, Sae Young Moon +1
Topic modeling is an effective technique for discovering hidden themes within documents and is widely used in text mining and data analysis across a variety of industry sectors. Re…
Industry-Aligned Granular Topic Modeling
Sae Young Moon, Myeongjun Erik Jang, Haoyan Luo +3
Topic modeling has extensive applications in text mining and data analysis across various industrial sectors. Although the concept of granularity holds significant value for busine…
Enhancing Privacy against Inversion Attacks in Federated Learning by using Mixing Gradients Strategies
Shaltiel Eloul, Fran Silavong, Sanket Kamthe +2
Federated learning reduces the risk of information leakage, but remains vulnerable to attacks. We investigate how several neural network design decisions can defend against gradien…
ST-FL: Style Transfer Preprocessing in Federated Learning for COVID-19 Segmentation
Antonios Georgiadis, Varun Babbar, Fran Silavong +2
Chest Computational Tomography (CT) scans present low cost, speed and objectivity for COVID-19 diagnosis and deep learning methods have shown great promise in assisting the analysi…
Senatus -- A Fast and Accurate Code-to-Code Recommendation Engine
Fran Silavong, Sean Moran, Antonios Georgiadis +2
Machine learning on source code (MLOnCode) is a popular research field that has been driven by the availability of large-scale code repositories and the development of powerful pro…