Mark Purcell

Publications

• MoJE: Mixture of Jailbreak Experts, Naive Tabular Classifiers as Guard for Prompt Attacks

  • • Giandomenico Cornacchia
    • Kieran Fraser
    • et al.
  • 2024
  • AIES 2024

• Pruning Federated Learning Models for Anomaly Detection in Resource-Constrained Environments

  • • Simone Magnani
    • Stefano Braghin
    • et al.
  • 2023
  • Big Data 2023

• Adaptive Aggregation For Federated Learning

  • • K. R. Kallapalayam Radhakrishnan
    • Vinod Muthusamy
    • et al.
  • 2022
  • Big Data 2022

• Machine Learning Platform for Extreme Scale Computing on Compressed IoT Data

  • • Seshu Tirupathi
    • Dhaval Salwala
    • et al.
  • 2022
  • Big Data 2022

• GOFLEX: Extracting, Aggregating and Trading Flexibility based on FlexOffers for 500+ Prosumers in 3 European cities [Operational Systems Paper]

  • • Bijay Neupane
    • Laurynas Siksnys
    • et al.
  • 2022
  • e-Energy 2022

• Towards an Accountable and Reproducible Federated Learning: A FactSheets Approach

  • • Nathalie Baracaldo Angel
    • Ali Anwar
    • et al.
  • 2022
  • arXiv

• Accountable Federated Machine Learning in Government: Engineering and Management Insights

  • • Dian Balta
    • Mahdi Sellami
    • et al.
  • 2021
  • ePart 2021

• Knowledge- And Data-driven Services for Energy Systems using Graph Neural Networks

  • • Francesco Fusco
    • Bradley Eck
    • et al.
  • 2020
  • Big Data 2020

• Power Saving Proxies for Web Servers

  • • Karl J. O'Dwyer
    • Eoin Creedon
    • et al.
  • 2019
  • Computer Journal

• AI modelling and time-series forecasting systems for trading energy flexibility in distribution grids

  • • Bradley Eck
    • Francesco Fusco
    • et al.
  • 2019
  • e-Energy 2019