Macarious Abadeer | IEEE Xplore Author Details. Macarious Abadeer. Affiliation. School of Computer Science, Carleton University, Ottawa, Canada. Publication ...
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Bidirectional Encoder Representations from Transformers (BERT) models achieve state-of-the-art performance on a number of Natural Language Processing tasks.
Dynamic Extraction of BERT-based Embeddings for the Detection of Malicious JavaScript · Author Picture Macarious Abadeer. Carleton University, Ottawa, Canada.
Abadeer, Macarious Philip Aziz. Abstract. We introduce FLightNER, a Federated Learning model that extends a state-of-the-art Named-Entity Recognition model ...
Bidirectional Encoder Representations from Transformers (BERT) models achieve state-of-the-art performance on a number of Natural Language Processing tasks.
Macarious Abadeer. 2020. Assessment of DistilBERT performance on Named Entity Recognition task for the detection of Protected Health Information and medical ...
Machine Learning-based Estimation of Story Points in Agile Development
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The goal of this paper is to evaluate a state-of-the-art machine learning technique, known as Deep-SE [3], for estimating story points in a commercial project.
Macarious Abadeer. MA. Macarious Abadeer. 0 followers. Follow. Presentations 0 Events 0 Followers 0 About. No presentations found. No events found. No followers ...
Name: Macarious Abadeer. School of Computer Science Carleton University, Ottawa, Canada. Project Outline. Privacy-Preserving Data Publishing (PPDP) is an ...
Jul 11, 2024 · Request PDF | On Dec 1, 2022, Macarious Abadeer and others published FLightNER: A Federated Learning Approach to Lightweight Named-Entity ...